ALL Preds
i=1
for(i in 1:length(dependentlist)){
dep=dependentlist[i]
print(dependentlist_eng[i])
load(paste("../data/modeldata/SVMorigmodeldatawithgeoandgeom_",dep,".RData",sep=""))
preds <- evaluateforwardCV_anyerror(mypath=paste("../data/FSCV/SVM_geoandgeom/SVMwithgeoandgeom_fw_5fold_10p_",dep,"_allpreds",sep=""),kk=1:5,endround = 10,error = "cverror",geheim = "geheimerprederror",yrange=c(0,1))
print(preds)
predictors <- c(as.character(preds[1,1]),as.character(preds[2,1]))
predict_radial_full(modeldata=origmodeldata, dependent=dep, predictors=predictors,kappasum = F,tausum = F)
predictors = vector()
for (n in 1:ncol(preds)){
for (n2 in 1:nrow(preds)){
predictors <- c(predictors,as.character(preds[n2,n]))
}
}
print("###################### WITH PREDICTORS from the FW SELECTION ###################")
uniquepredictors <- unique(predictors)
predict_radial_full(modeldata=origmodeldata, dependent=dep, predictors=uniquepredictors)
print("######################WITH ALL PREDICTORS###################")
predict_radial_full(modeldata=origmodeldata, dependent=dep, predictors=unlist(paramsets[5]),printpreds = FALSE)
rm(origmodeldata,paramsets,paramsetnames,dependent)
}
## [1] "1a.2.1 - Potential as a habitat for drought-tolerant species"
## [1] "Prediction error at end is: 0.646753246753247"
## [2] "Prediction error at end is: 0.637662337662338"
## [3] "Prediction error at end is: 0.675324675324675"
## [4] "Prediction error at end is: 0.657142857142857"
## [5] "Prediction error at end is: 0.648051948051948"
## [6] "Prediction error at end is: 0.657142857142857"
## [7] "Prediction error at end is: 0.648051948051948"
## [8] "Prediction error at end is: 0.620779220779221"
## [9] "Prediction error at end is: 0.620779220779221"
## [10] "Prediction error at end is: 0.610822510822511"
## k 1
## 1 TRI_hr_ws25
## 2 geom_10m_fl4_L37
## 3 TRI_hr_ws42
## 4 Slope_Height_hr
## 5 profc_ws13_hr_hr
## 6 longc_ws5_hr_hr
## 7 Channel_Network_Base_Level_50m
## 8 geom_hr_L50m_fl1_rplipshannon_UE_hr_10cells_hr
## 9 Convexity_10m
## 10 slope_DTM_50m_avg_ws9_50m
## k 2
## 1 geom_hr_L50m_fl1_rpliprichness_UE_hr_20cells_hr
## 2 Standardized_Height_50m
## 3 Normalized_Height_50m
## 4 elev_ws15_10m
## 5 geom_hr_L3_fl1_rplipmps_UE_hr_10cells_hr
## 6 geom_hr_L3_fl10_rplipdominance_UE_hr_5cells_hr
## 7 geom_hr_L50m_fl10_rplipsimpson_UE_hr_40cells_hr
## 8 ProfileCurvature_10m
## 9 minic_ws15_hr_hr
## 10 fischerk_ws61_hr
## k 3
## 1 geom_10m_fl4_L9
## 2 geom_hr_L50m_fl10_rplipsimpson_UE_hr_60cells_hr
## 3 slope_DTM_50m_avg_ws7_50m
## 4 Longitudinal_Curvature_hr
## 5 dtm_hr_TEXTURE_r10
## 6 Texture_50m
## 7 crosc_ws11_10m
## 8 minic_ws5_hr_hr
## 9 ProfileCurvature_10m
## 10 geom_dtm_10m_hyd_fl5_L70
## k 4
## 1 geom_dtm_10m_hyd_fl5_L16
## 2 Slope_Height_hr
## 3 profc_ws5_hr_hr
## 4 MRVBF_hr
## 5 geom_hr_L50m_fl10_rpliprichness_UE_hr_20cells_hr
## 6 elev_ws11_10m
## 7 crosc_ws3_10m
## 8 crosc_ws3_hr_hr
## 9 TRI_hr_ws18
## 10 fischerk_ws3_hr
## k 5
## 1 geom_10m_fl4_L9
## 2 dtm_hr_TEXTURE_r20
## 3 Longitudinal_Curvature_hr
## 4 geom_hr_L3_fl10_rplipedgedensity_UE_hr_60cells_hr
## 5 GeneralCurvature_10m
## 6 Flow_Line_Curvature_hr
## 7 geom_hr_L50m_fl10_rplippatchdensity_UE_hr_60cells_hr
## 8 crosc_DTM_50m_avg_ws9_50m
## 9 crosc_DTM_50m_avg_ws11_50m
## 10 elev_ws15_10m
## [1] "10fold cv-error: 0.583333333333333"
## [1] "For predictors TRI_hr_ws25 AND geom_10m_fl4_L37"
##
## preds 1 2 3 4 5
## 1 0 0 0 0 0
## 2 0 0 0 0 0
## 3 0 0 0 0 0
## 4 4 12 20 33 16
## 5 0 1 1 5 16
## [1] "Kappa overall = 0.172252533125487"
## [1] "Tau overall = 0.31712962962963"
## [1] "mean quality = 0.155384615384615"
## [1] "The quality is 0.155384615384615"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = NaN"
## [1] "###################### WITH PREDICTORS from the FW SELECTION ###################"
## [1] "10fold cv-error: 0.564814814814815"
## [1] "For predictors TRI_hr_ws25 AND geom_10m_fl4_L37 AND TRI_hr_ws42 AND Slope_Height_hr AND profc_ws13_hr_hr AND longc_ws5_hr_hr AND Channel_Network_Base_Level_50m AND geom_hr_L50m_fl1_rplipshannon_UE_hr_10cells_hr AND Convexity_10m AND slope_DTM_50m_avg_ws9_50m AND geom_hr_L50m_fl1_rpliprichness_UE_hr_20cells_hr AND Standardized_Height_50m AND Normalized_Height_50m AND elev_ws15_10m AND geom_hr_L3_fl1_rplipmps_UE_hr_10cells_hr AND geom_hr_L3_fl10_rplipdominance_UE_hr_5cells_hr AND geom_hr_L50m_fl10_rplipsimpson_UE_hr_40cells_hr AND ProfileCurvature_10m AND minic_ws15_hr_hr AND fischerk_ws61_hr AND geom_10m_fl4_L9 AND geom_hr_L50m_fl10_rplipsimpson_UE_hr_60cells_hr AND slope_DTM_50m_avg_ws7_50m AND Longitudinal_Curvature_hr AND dtm_hr_TEXTURE_r10 AND Texture_50m AND crosc_ws11_10m AND minic_ws5_hr_hr AND geom_dtm_10m_hyd_fl5_L70 AND geom_dtm_10m_hyd_fl5_L16 AND profc_ws5_hr_hr AND MRVBF_hr AND geom_hr_L50m_fl10_rpliprichness_UE_hr_20cells_hr AND elev_ws11_10m AND crosc_ws3_10m AND crosc_ws3_hr_hr AND TRI_hr_ws18 AND fischerk_ws3_hr AND dtm_hr_TEXTURE_r20 AND geom_hr_L3_fl10_rplipedgedensity_UE_hr_60cells_hr AND GeneralCurvature_10m AND Flow_Line_Curvature_hr AND geom_hr_L50m_fl10_rplippatchdensity_UE_hr_60cells_hr AND crosc_DTM_50m_avg_ws9_50m AND crosc_DTM_50m_avg_ws11_50m"
##
## preds 1 2 3 4 5
## 1 1 0 0 0 0
## 2 0 5 0 0 0
## 3 1 0 8 0 0
## 4 2 7 12 37 12
## 5 0 1 1 1 20
## [1] "Kappa overall = 0.501123595505618"
## [1] "Tau overall = 0.571759259259259"
## [1] "mean quality = 0.41816141604874"
## [1] "The quality is 0.41816141604874"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = 0.569230450224967"
## [1] "######################WITH ALL PREDICTORS###################"
## [1] "10fold cv-error: 0.564814814814815"
##
## preds 1 2 3 4 5
## 1 0 0 0 0 0
## 2 0 1 0 0 0
## 3 0 0 0 0 0
## 4 4 11 20 36 17
## 5 0 1 1 2 15
## [1] "Kappa overall = 0.214443434212235"
## [1] "Tau overall = 0.351851851851852"
## [1] "mean quality = 0.178717948717949"
## [1] "The quality is 0.178717948717949"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect

## [1] "######### Cramer's V = NaN"
## [1] "1a.2.2 - Potential as a habitat for moisture-tolerant species"
## [1] "Prediction error at end is: 0.61991341991342"
## [2] "Prediction error at end is: 0.628571428571429"
## [3] "Prediction error at end is: 0.647619047619048"
## [4] "Prediction error at end is: 0.685714285714286"
## [5] "Prediction error at end is: 0.648484848484848"
## [6] "Prediction error at end is: 0.667099567099567"
## [7] "Prediction error at end is: 0.638095238095238"
## [8] "Prediction error at end is: 0.627705627705628"
## [9] "Prediction error at end is: 0.628138528138528"
## [10] "Prediction error at end is: 0.637662337662338"
## k 1
## 1 geom_10m_fl8_L12
## 2 Longitudinal_Curvature_hr
## 3 geom_hr_L50m_fl1_rplipshannon_UE_hr_40cells_hr
## 4 Catchment_Area_hr
## 5 terraintexture_hr_ws33_tp25
## 6 terraintexture_hr_ws17_tp25
## 7 planc_DTM_50m_avg_ws3_50m
## 8 geom_hr_L50m_fl1_rplipmps_UE_hr_20cells_hr
## 9 geom_hr_L50m_fl1_rplipmps_UE_hr_40cells_hr
## 10 slope_DTM_50m_avg_ws3_50m
## k 2
## 1 geom_10m_fl10_L27
## 2 vectorruggedness_hr_ws59
## 3 geom_hr_L3_fl1_rplipdominance_UE_hr_10cells_hr
## 4 geom_hr_L50m_fl10_rplipdominance_UE_hr_60cells_hr
## 5 geom_hr_L50m_fl1_rplipmps_UE_hr_60cells_hr
## 6 geom_10m_fl10_L80
## 7 StandardizedHeight_10m
## 8 Catchment_Area_hr
## 9 minic_ws5_10m
## 10 Convergence_Index_hr
## k 3
## 1 Vertical_Distance_to_Channel_Network_50m
## 2 geom_hr_L50m_fl1_rplipdominance_UE_hr_40cells_hr
## 3 Longitudinal_Curvature_hr
## 4 sagaTopographic_Wetness_Index_50m
## 5 geom_10m_fl8_L9
## 6 Convexity_50m
## 7 profc_ws11_hr_hr
## 8 longc_ws5_hr_hr
## 9 profc_ws3_10m
## 10 geom_hr_L3_fl10_rplippatchdensity_UE_hr_40cells_hr
## k 4
## 1 geom_10m_fl10_L70
## 2 Longitudinal_Curvature_hr
## 3 Catchment_area_50m
## 4 geom_hr_L50m_fl1_rplipdominance_UE_hr_40cells_hr
## 5 vectorruggedness_hr_ws35
## 6 VerticalDistancetoChannelNetwork_10m
## 7 planc_DTM_50m_avg_ws11_50m
## 8 MRRTF_hr
## 9 geom_10m_fl3_L46
## 10 minic_ws3_hr_hr
## k 5
## 1 elev_ws11_10m
## 2 geom_hr_L3_fl1_rplipdominance_UE_hr_10cells_hr
## 3 sagaTopographic_Wetness_Index_50m
## 4 minic_ws7_hr_hr
## 5 Valley_Depth_hr
## 6 geom_hr_L3_fl10_rplipmps_UE_hr_40cells_hr
## 7 geom_hr_L50m_fl10_rplipmps_UE_hr_5cells_hr
## 8 MassBalanceIndex_10m
## 9 geom_hr_L50m_fl1_rplipmps_UE_hr_20cells_hr
## 10 planc_DTM_50m_avg_ws11_50m
## [1] "10fold cv-error: 0.5"
## [1] "For predictors geom_10m_fl8_L12 AND Longitudinal_Curvature_hr"
##
## preds 2 3 4 5
## 2 23 10 8 1
## 3 0 0 0 0
## 4 10 12 26 10
## 5 0 1 1 6
## [1] "Kappa overall = 0.294378698224852"
## [1] "Tau overall = 0.345679012345679"
## [1] "mean quality = 0.28653921687111"
## [1] "The quality is 0.28653921687111"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = NaN"
## [1] "###################### WITH PREDICTORS from the FW SELECTION ###################"
## [1] "10fold cv-error: 0.472222222222222"
## [1] "For predictors geom_10m_fl8_L12 AND Longitudinal_Curvature_hr AND geom_hr_L50m_fl1_rplipshannon_UE_hr_40cells_hr AND Catchment_Area_hr AND terraintexture_hr_ws33_tp25 AND terraintexture_hr_ws17_tp25 AND planc_DTM_50m_avg_ws3_50m AND geom_hr_L50m_fl1_rplipmps_UE_hr_20cells_hr AND geom_hr_L50m_fl1_rplipmps_UE_hr_40cells_hr AND slope_DTM_50m_avg_ws3_50m AND geom_10m_fl10_L27 AND vectorruggedness_hr_ws59 AND geom_hr_L3_fl1_rplipdominance_UE_hr_10cells_hr AND geom_hr_L50m_fl10_rplipdominance_UE_hr_60cells_hr AND geom_hr_L50m_fl1_rplipmps_UE_hr_60cells_hr AND geom_10m_fl10_L80 AND StandardizedHeight_10m AND minic_ws5_10m AND Convergence_Index_hr AND Vertical_Distance_to_Channel_Network_50m AND geom_hr_L50m_fl1_rplipdominance_UE_hr_40cells_hr AND sagaTopographic_Wetness_Index_50m AND geom_10m_fl8_L9 AND Convexity_50m AND profc_ws11_hr_hr AND longc_ws5_hr_hr AND profc_ws3_10m AND geom_hr_L3_fl10_rplippatchdensity_UE_hr_40cells_hr AND geom_10m_fl10_L70 AND Catchment_area_50m AND vectorruggedness_hr_ws35 AND VerticalDistancetoChannelNetwork_10m AND planc_DTM_50m_avg_ws11_50m AND MRRTF_hr AND geom_10m_fl3_L46 AND minic_ws3_hr_hr AND elev_ws11_10m AND minic_ws7_hr_hr AND Valley_Depth_hr AND geom_hr_L3_fl10_rplipmps_UE_hr_40cells_hr AND geom_hr_L50m_fl10_rplipmps_UE_hr_5cells_hr AND MassBalanceIndex_10m"
##
## preds 2 3 4 5
## 2 30 9 6 1
## 3 0 8 0 1
## 4 3 5 28 7
## 5 0 1 1 8
## [1] "Kappa overall = 0.55566311713456"
## [1] "Tau overall = 0.580246913580247"
## [1] "mean quality = 0.481657715717866"
## [1] "The quality is 0.481657715717866"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = 0.58082023643375"
## [1] "######################WITH ALL PREDICTORS###################"
## [1] "10fold cv-error: 0.611111111111111"
##
## preds 2 3 4 5
## 2 23 13 9 2
## 3 0 0 0 0
## 4 10 10 26 15
## 5 0 0 0 0
## [1] "Kappa overall = 0.201303584858361"
## [1] "Tau overall = 0.271604938271605"
## [1] "mean quality = 0.193734335839599"
## [1] "The quality is 0.193734335839599"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect

## [1] "######### Cramer's V = NaN"
## [1] "1a.3 - Habitat for soil organisms"
## [1] "Prediction error at end is: 0.511688311688312"
## [2] "Prediction error at end is: 0.482251082251082"
## [3] "Prediction error at end is: 0.453679653679654"
## [4] "Prediction error at end is: 0.425974025974026"
## [5] "Prediction error at end is: 0.389177489177489"
## [6] "Prediction error at end is: 0.398268398268398"
## [7] "Prediction error at end is: 0.380519480519481"
## [8] "Prediction error at end is: 0.416450216450216"
## [9] "Prediction error at end is: 0.361471861471861"
## [10] "Prediction error at end is: 0.389177489177489"
## k 1
## 1 Channel_Network_Base_Level_hr
## 2 Convexity_50m
## 3 geom_hr_L3_fl10_rplipdominance_UE_hr_60cells_hr
## 4 Slope_hr
## 5 Texture_50m
## 6 Maximal_Curvature_hr
## 7 Valley_Depth_hr
## 8 slope_DTM_50m_avg_ws5_50m
## 9 Vertical_Distance_to_Channel_Network_50m
## 10 geom_hr_L50m_fl10_rplipdominance_UE_hr_5cells_hr
## k 2
## 1 Channel_Network_Base_Level_hr
## 2 Normalized_Height_50m
## 3 Slope_50m
## 4 geom_hr_L3_fl1_rpliprichness_UE_hr_5cells_hr
## 5 terraintexture_hr_ws57_tp25
## 6 Normalized_Height_hr
## 7 StandardizedHeight_10m
## 8 fischerk_ws23_hr
## 9 Texture_50m
## 10 geom_dtm_10m_hyd_fl5_L6
## k 3
## 1 elev_ws11_10m
## 2 NormalizedHeight_10m
## 3 TangentialCurvature_10m
## 4 Convexity_50m
## 5 terraintexture_hr_ws57_tp25
## 6 Catchment_slope_50m
## 7 geom_hr_L3_fl10_rplipdominance_UE_hr_60cells_hr
## 8 vectorruggedness_hr_ws7
## 9 Topographic_Wetness_Index_50m
## 10 minic_ws7_hr_hr
## k 4
## 1 SGU
## 2 Channel_Network_Base_Level_50m
## 3 NormalizedHeight_10m
## 4 vectorruggedness_hr_ws3
## 5 minic_ws29_hr_hr
## 6 geom_hr_L3_fl1_rplippatchdensity_UE_hr_60cells_hr
## 7 geom_hr_L3_fl10_rpliprichness_UE_hr_20cells_hr
## 8 StandardizedHeight_10m
## 9 geom_hr_L3_fl10_rplipdominance_UE_hr_60cells_hr
## 10 Normalized_Height_50m
## k 5
## 1 minic_ws7_hr_hr
## 2 NormalizedHeight_10m
## 3 terraintexture_hr_ws45_tp25
## 4 maxic_ws7_10m
## 5 geom_hr_L50m_fl1_rplipdominance_UE_hr_60cells_hr
## 6 geom_hr_L50m_fl1_rplipmps_UE_hr_40cells_hr
## 7 planc_DTM_50m_avg_ws9_50m
## 8 slope_DTM_50m_avg_ws7_50m
## 9 slope_DTM_50m_avg_ws3_50m
## 10 Catchment_slope_50m
## [1] "10fold cv-error: 0.435185185185185"
## [1] "For predictors Channel_Network_Base_Level_hr AND Convexity_50m"
##
## preds 1 2 3 4
## 1 12 3 1 3
## 2 11 31 6 1
## 3 0 0 12 4
## 4 1 0 7 16
## [1] "Kappa overall = 0.532631578947368"
## [1] "Tau overall = 0.54320987654321"
## [1] "mean quality = 0.470812655086849"
## [1] "The quality is 0.470812655086849"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = 0.569455556051712"
## [1] "###################### WITH PREDICTORS from the FW SELECTION ###################"
## [1] "10fold cv-error: 0.305555555555556"
## [1] "For predictors Channel_Network_Base_Level_hr AND Convexity_50m AND geom_hr_L3_fl10_rplipdominance_UE_hr_60cells_hr AND Slope_hr AND Texture_50m AND Maximal_Curvature_hr AND Valley_Depth_hr AND slope_DTM_50m_avg_ws5_50m AND Vertical_Distance_to_Channel_Network_50m AND geom_hr_L50m_fl10_rplipdominance_UE_hr_5cells_hr AND Normalized_Height_50m AND Slope_50m AND geom_hr_L3_fl1_rpliprichness_UE_hr_5cells_hr AND terraintexture_hr_ws57_tp25 AND Normalized_Height_hr AND StandardizedHeight_10m AND fischerk_ws23_hr AND geom_dtm_10m_hyd_fl5_L6 AND elev_ws11_10m AND NormalizedHeight_10m AND TangentialCurvature_10m AND Catchment_slope_50m AND vectorruggedness_hr_ws7 AND Topographic_Wetness_Index_50m AND minic_ws7_hr_hr AND SGU AND Channel_Network_Base_Level_50m AND vectorruggedness_hr_ws3 AND minic_ws29_hr_hr AND geom_hr_L3_fl1_rplippatchdensity_UE_hr_60cells_hr AND geom_hr_L3_fl10_rpliprichness_UE_hr_20cells_hr AND terraintexture_hr_ws45_tp25 AND maxic_ws7_10m AND geom_hr_L50m_fl1_rplipdominance_UE_hr_60cells_hr AND geom_hr_L50m_fl1_rplipmps_UE_hr_40cells_hr AND planc_DTM_50m_avg_ws9_50m AND slope_DTM_50m_avg_ws7_50m AND slope_DTM_50m_avg_ws3_50m"
##
## preds 1 2 3 4
## 1 22 4 0 0
## 2 2 30 4 2
## 3 0 0 19 2
## 4 0 0 3 20
## [1] "Kappa overall = 0.787745664739884"
## [1] "Tau overall = 0.790123456790123"
## [1] "mean quality = 0.729828042328042"
## [1] "The quality is 0.729828042328042"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = 0.800853249082389"
## [1] "######################WITH ALL PREDICTORS###################"
## [1] "10fold cv-error: 0.5"
##
## preds 1 2 3 4
## 1 0 0 0 0
## 2 24 34 6 11
## 3 0 0 20 9
## 4 0 0 0 4
## [1] "Kappa overall = 0.346563407550823"
## [1] "Tau overall = 0.382716049382716"
## [1] "mean quality = 0.297857142857143"
## [1] "The quality is 0.297857142857143"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect

## [1] "######### Cramer's V = NaN"
## [1] "1a.4 - Habitat for crops"
## [1] "Prediction error at end is: 0.177056277056277"
## [2] "Prediction error at end is: 0.167099567099567"
## [3] "Prediction error at end is: 0.176190476190476"
## [4] "Prediction error at end is: 0.185281385281385"
## [5] "Prediction error at end is: 0.176190476190476"
## [6] "Prediction error at end is: 0.176190476190476"
## [7] "Prediction error at end is: 0.167099567099567"
## [8] "Prediction error at end is: 0.176190476190476"
## [9] "Prediction error at end is: 0.176190476190476"
## [10] "Prediction error at end is: 0.176190476190476"
## k 1
## 1 slope_ws3_hr_hr
## 2 slope_ws15_10m
## 3 geom_hr_L3_fl10_rplipdominance_UE_hr_40cells_hr
## 4 geom_hr_L3_fl10_rplipdominance_UE_hr_10cells_hr
## 5 terraintexture_hr_ws53_tp5
## 6 terraintexture_hr_ws57_tp5
## 7 minic_ws11_10m
## 8 Flow_Line_Curvature_hr
## 9 SlopeHeight_10m
## 10 Convexity_50m
## k 2
## 1 geom_10m_fl10_L6
## 2 TRI_hr_ws2
## 3 Slope_50m
## 4 geom_hr_L3_fl10_rpliprichness_UE_hr_60cells_hr
## 5 geom_hr_L3_fl1_rplipedgedensity_UE_hr_60cells_hr
## 6 geom_hr_L3_fl1_rplipshannon_UE_hr_60cells_hr
## 7 geom_hr_L50m_fl10_rplipshannon_UE_hr_60cells_hr
## 8 geom_hr_L50m_fl10_rplipsimpson_UE_hr_60cells_hr
## 9 slope_DTM_50m_avg_ws7_50m
## 10 TRI_hr_ws57
## k 3
## 1 slope_ws3_hr_hr
## 2 Slope_hr
## 3 slope_ws5_hr_hr
## 4 geom_10m_fl1_L11
## 5 Convexity_10m
## 6 geom_10m_fl10_L110
## 7 geom_hr_L3_fl10_rpliprichness_UE_hr_60cells_hr
## 8 minic_DTM_50m_avg_ws3_50m
## 9 profc_DTM_50m_avg_ws3_50m
## 10 geom_10m_fl8_L3
## k 4
## 1 slope_ws3_hr_hr
## 2 geom_hr_L3_fl10_rplippatchdensity_UE_hr_40cells_hr
## 3 terraintexture_hr_ws57_tp5
## 4 TRI_hr_ws14
## 5 TRI_hr_ws9
## 6 LS_Factor_50m
## 7 geom_hr_L50m_fl10_rplipdominance_UE_hr_20cells_hr
## 8 geom_hr_L3_fl10_rpliprichness_UE_hr_60cells_hr
## 9 slope_DTM_50m_avg_ws7_50m
## 10 geom_10m_fl1_L4
## k 5
## 1 TRI_hr_ws10
## 2 terraintexture_hr_ws37_tp25
## 3 Convexity_10m
## 4 terraintexture_hr_ws17_tp25
## 5 fischerk_ws7_hr
## 6 TRI_hr_ws38
## 7 vectorstrength_hr_ws7_hr
## 8 planc_DTM_50m_avg_ws3_50m
## 9 geom_hr_L50m_fl1_rplipmps_UE_hr_40cells_hr
## 10 geom_hr_L50m_fl1_rplippatchdensity_UE_hr_20cells_hr
## [1] "10fold cv-error: 0.175925925925926"
## [1] "For predictors slope_ws3_hr_hr AND slope_ws15_10m"
##
## preds 3 4 5
## 3 0 0 0
## 4 7 61 6
## 5 1 1 32
## [1] "Kappa overall = 0.719917012448133"
## [1] "Tau overall = 0.791666666666667"
## [1] "mean quality = 0.537777777777778"
## [1] "The quality is 0.537777777777778"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = NaN"
## [1] "###################### WITH PREDICTORS from the FW SELECTION ###################"
## [1] "10fold cv-error: 0.12962962962963"
## [1] "For predictors slope_ws3_hr_hr AND slope_ws15_10m AND geom_hr_L3_fl10_rplipdominance_UE_hr_40cells_hr AND geom_hr_L3_fl10_rplipdominance_UE_hr_10cells_hr AND terraintexture_hr_ws53_tp5 AND terraintexture_hr_ws57_tp5 AND minic_ws11_10m AND Flow_Line_Curvature_hr AND SlopeHeight_10m AND Convexity_50m AND geom_10m_fl10_L6 AND TRI_hr_ws2 AND Slope_50m AND geom_hr_L3_fl10_rpliprichness_UE_hr_60cells_hr AND geom_hr_L3_fl1_rplipedgedensity_UE_hr_60cells_hr AND geom_hr_L3_fl1_rplipshannon_UE_hr_60cells_hr AND geom_hr_L50m_fl10_rplipshannon_UE_hr_60cells_hr AND geom_hr_L50m_fl10_rplipsimpson_UE_hr_60cells_hr AND slope_DTM_50m_avg_ws7_50m AND TRI_hr_ws57 AND Slope_hr AND slope_ws5_hr_hr AND geom_10m_fl1_L11 AND Convexity_10m AND geom_10m_fl10_L110 AND minic_DTM_50m_avg_ws3_50m AND profc_DTM_50m_avg_ws3_50m AND geom_10m_fl8_L3 AND geom_hr_L3_fl10_rplippatchdensity_UE_hr_40cells_hr AND TRI_hr_ws14 AND TRI_hr_ws9 AND LS_Factor_50m AND geom_hr_L50m_fl10_rplipdominance_UE_hr_20cells_hr AND geom_10m_fl1_L4 AND TRI_hr_ws10 AND terraintexture_hr_ws37_tp25 AND terraintexture_hr_ws17_tp25 AND fischerk_ws7_hr AND TRI_hr_ws38 AND vectorstrength_hr_ws7_hr AND planc_DTM_50m_avg_ws3_50m AND geom_hr_L50m_fl1_rplipmps_UE_hr_40cells_hr AND geom_hr_L50m_fl1_rplippatchdensity_UE_hr_20cells_hr"
##
## preds 3 4 5
## 3 0 0 0
## 4 8 62 4
## 5 0 0 34
## [1] "Kappa overall = 0.775933609958506"
## [1] "Tau overall = 0.833333333333333"
## [1] "mean quality = 0.577524893314367"
## [1] "The quality is 0.577524893314367"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = NaN"
## [1] "######################WITH ALL PREDICTORS###################"
## [1] "10fold cv-error: 0.212962962962963"
##
## preds 3 4 5
## 3 0 0 0
## 4 8 62 5
## 5 0 0 33
## [1] "Kappa overall = 0.75625"
## [1] "Tau overall = 0.819444444444444"
## [1] "mean quality = 0.565029239766082"
## [1] "The quality is 0.565029239766082"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect

## [1] "######### Cramer's V = NaN"
## [1] "1c.1 - Average precipitation retention capacity"
## [1] "Prediction error at end is: 0.565367965367965"
## [2] "Prediction error at end is: 0.593073593073593"
## [3] "Prediction error at end is: 0.593073593073593"
## [4] "Prediction error at end is: 0.62034632034632"
## [5] "Prediction error at end is: 0.620779220779221"
## [6] "Prediction error at end is: 0.648051948051948"
## [7] "Prediction error at end is: 0.648051948051948"
## [8] "Prediction error at end is: 0.648051948051948"
## [9] "Prediction error at end is: 0.657142857142857"
## [10] "Prediction error at end is: 0.638528138528139"
## k 1
## 1 slope_ws15_10m
## 2 GeneralCurvature_10m
## 3 TRI_hr_ws49
## 4 minic_ws15_10m
## 5 ProfileCurvature_10m
## 6 geom_hr_L50m_fl1_rplipdominance_UE_hr_10cells_hr
## 7 terraintexture_hr_ws37_tp25
## 8 profc_DTM_50m_avg_ws5_50m
## 9 fischerk_ws19_hr
## 10 geom_hr_L50m_fl1_rplippatchdensity_UE_hr_20cells_hr
## k 2
## 1 crosc_ws5_10m
## 2 Channel_Network_Base_Level_50m
## 3 ValleyDepth_hr
## 4 planc_ws13_hr_hr
## 5 geom_hr_L50m_fl10_rplipsimpson_UE_hr_10cells_hr
## 6 crosc_ws11_10m
## 7 elev_ws11_10m
## 8 crosc_ws3_10m
## 9 Plan_Curvature_hr
## 10 CrossSectionalCurvature_hr
## k 3
## 1 Flow_Line_Curvature_50m
## 2 geom_hr_L50m_fl10_rplippatchdensity_UE_hr_10cells_hr
## 3 vectorruggedness_hr_ws57
## 4 geom_hr_L3_fl1_rpliprichness_UE_hr_60cells_hr
## 5 profc_DTM_50m_avg_ws9_50m
## 6 planc_ws7_hr_hr
## 7 ValleyDepth_hr
## 8 longc_ws3_10m
## 9 Plan_Curvature_hr
## 10 Slope_50m
## k 4
## 1 slope_DTM_50m_avg_ws7_50m
## 2 geom_hr_L50m_fl1_rplipmps_UE_hr_40cells_hr
## 3 LSFactor_10m
## 4 RelativeSlopePosition_10m
## 5 geom_hr_L50m_fl1_rplipdominance_UE_hr_10cells_hr
## 6 Plan_Curvature_hr
## 7 geom_10m_fl3_L50
## 8 LS_Factor_hr
## 9 ValleyDepth_hr
## 10 geom_hr_L3_fl1_rplipshannon_UE_hr_40cells_hr
## k 5
## 1 Flow_Line_Curvature_50m
## 2 geom_hr_L50m_fl1_rpliprichness_UE_hr_20cells_hr
## 3 maxic_ws15_hr_hr
## 4 Slope_Height_50m
## 5 geom_hr_L3_fl1_rplipdominance_UE_hr_60cells_hr
## 6 geom_hr_L3_fl10_rplipdominance_UE_hr_5cells_hr
## 7 Plan_Curvature_hr
## 8 minic_ws3_hr_hr
## 9 TRI_hr_ws42
## 10 TRI_hr_ws43
## [1] "10fold cv-error: 0.555555555555556"
## [1] "For predictors slope_ws15_10m AND GeneralCurvature_10m"
##
## preds 1 2 3 4 5
## 1 10 0 3 1 2
## 2 16 44 9 13 4
## 3 0 0 0 0 0
## 4 0 1 0 4 0
## 5 0 0 0 0 1
## [1] "Kappa overall = 0.273176761433869"
## [1] "Tau overall = 0.43287037037037"
## [1] "mean quality = 0.23432611701668"
## [1] "The quality is 0.23432611701668"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = NaN"
## [1] "###################### WITH PREDICTORS from the FW SELECTION ###################"
## [1] "10fold cv-error: 0.537037037037037"
## [1] "For predictors slope_ws15_10m AND GeneralCurvature_10m AND TRI_hr_ws49 AND minic_ws15_10m AND ProfileCurvature_10m AND geom_hr_L50m_fl1_rplipdominance_UE_hr_10cells_hr AND terraintexture_hr_ws37_tp25 AND profc_DTM_50m_avg_ws5_50m AND fischerk_ws19_hr AND geom_hr_L50m_fl1_rplippatchdensity_UE_hr_20cells_hr AND crosc_ws5_10m AND Channel_Network_Base_Level_50m AND ValleyDepth_hr AND planc_ws13_hr_hr AND geom_hr_L50m_fl10_rplipsimpson_UE_hr_10cells_hr AND crosc_ws11_10m AND elev_ws11_10m AND crosc_ws3_10m AND Plan_Curvature_hr AND CrossSectionalCurvature_hr AND Flow_Line_Curvature_50m AND geom_hr_L50m_fl10_rplippatchdensity_UE_hr_10cells_hr AND vectorruggedness_hr_ws57 AND geom_hr_L3_fl1_rpliprichness_UE_hr_60cells_hr AND profc_DTM_50m_avg_ws9_50m AND planc_ws7_hr_hr AND longc_ws3_10m AND Slope_50m AND slope_DTM_50m_avg_ws7_50m AND geom_hr_L50m_fl1_rplipmps_UE_hr_40cells_hr AND LSFactor_10m AND RelativeSlopePosition_10m AND geom_10m_fl3_L50 AND LS_Factor_hr AND geom_hr_L3_fl1_rplipshannon_UE_hr_40cells_hr AND geom_hr_L50m_fl1_rpliprichness_UE_hr_20cells_hr AND maxic_ws15_hr_hr AND Slope_Height_50m AND geom_hr_L3_fl1_rplipdominance_UE_hr_60cells_hr AND geom_hr_L3_fl10_rplipdominance_UE_hr_5cells_hr AND minic_ws3_hr_hr AND TRI_hr_ws42 AND TRI_hr_ws43"
##
## preds 1 2 3 4 5
## 1 18 0 3 0 3
## 2 8 45 9 12 3
## 3 0 0 0 0 0
## 4 0 0 0 6 0
## 5 0 0 0 0 1
## [1] "Kappa overall = 0.449865951742627"
## [1] "Tau overall = 0.560185185185185"
## [1] "mean quality = 0.324621212121212"
## [1] "The quality is 0.324621212121212"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = NaN"
## [1] "######################WITH ALL PREDICTORS###################"
## [1] "10fold cv-error: 0.583333333333333"
##
## preds 1 2 3 4 5
## 1 3 0 0 1 1
## 2 23 45 12 17 6
## 3 0 0 0 0 0
## 4 0 0 0 0 0
## 5 0 0 0 0 0
## [1] "Kappa overall = 0.0607334396289316"
## [1] "Tau overall = 0.305555555555555"
## [1] "mean quality = 0.10880721220527"
## [1] "The quality is 0.10880721220527"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect

## [1] "######### Cramer's V = NaN"
## [1] "1c.1 - Minimum precipitation retention capacity"
## [1] "Prediction error at end is: 0.805194805194805"
## [2] "Prediction error at end is: 0.769264069264069"
## [3] "Prediction error at end is: 0.776190476190476"
## [4] "Prediction error at end is: 0.767965367965368"
## [5] "Prediction error at end is: 0.777922077922078"
## [6] "Prediction error at end is: 0.758874458874459"
## [7] "Prediction error at end is: 0.758874458874459"
## [8] "Prediction error at end is: 0.768398268398268"
## [9] "Prediction error at end is: 0.741125541125541"
## [10] "Prediction error at end is: 0.693939393939394"
## k 1
## 1 geom_hr_L50m_fl10_rplipdominance_UE_hr_40cells_hr
## 2 vectorruggedness_hr_ws23
## 3 geom_hr_L50m_fl10_rpliprichness_UE_hr_40cells_hr
## 4 geom_hr_L50m_fl1_rplipmps_UE_hr_40cells_hr
## 5 CrossSectionalCurvature_hr
## 6 geom_hr_L50m_fl10_rplipedgedensity_UE_hr_60cells_hr
## 7 geom_hr_L3_fl10_rplipdominance_UE_hr_60cells_hr
## 8 geom_hr_L3_fl10_rplipdominance_UE_hr_5cells_hr
## 9 Total_Curvature_50m
## 10 profc_ws11_10m
## k 2
## 1 geom_hr_L3_fl10_rpliprichness_UE_hr_60cells_hr
## 2 minic_ws11_10m
## 3 planc_ws5_10m
## 4 vectorruggedness_hr_ws33
## 5 minic_DTM_50m_avg_ws7_50m
## 6 slope_ws5_hr_hr
## 7 planc_ws29_hr_hr
## 8 maxic_ws23_hr_hr
## 9 planc_ws23_hr_hr
## 10 crosc_ws11_10m
## k 3
## 1 geom_hr_L50m_fl1_rpliprichness_UE_hr_60cells_hr
## 2 crosc_DTM_50m_avg_ws3_50m
## 3 geom_hr_L50m_fl1_rplipmps_UE_hr_20cells_hr
## 4 geom_hr_L50m_fl1_rplipsimpson_UE_hr_40cells_hr
## 5 maxic_ws11_10m
## 6 geom_hr_L50m_fl1_rplipsimpson_UE_hr_60cells_hr
## 7 Tangential_Curvature_50m
## 8 geom_hr_L3_fl1_rplipmps_UE_hr_10cells_hr
## 9 minic_ws15_10m
## 10 geom_hr_L50m_fl1_rplippatchdensity_UE_hr_60cells_hr
## k 4
## 1 geom_hr_L50m_fl10_rplipsimpson_UE_hr_20cells_hr
## 2 geom_hr_L50m_fl1_rplipshannon_UE_hr_40cells_hr
## 3 Vertical_Distance_to_Channel_Network_50m
## 4 profc_ws15_10m
## 5 planc_ws11_10m
## 6 geom_hr_L50m_fl1_rplipedgedensity_UE_hr_40cells_hr
## 7 Relative_Slope_Position_hr
## 8 geom_hr_L50m_fl1_rpliprichness_UE_hr_60cells_hr
## 9 geom_hr_L50m_fl1_rplipmps_UE_hr_10cells_hr
## 10 Catchment_area_50m
## k 5
## 1 geom_hr_L3_fl10_rplippatchdensity_UE_hr_20cells_hr
## 2 geom_hr_L50m_fl1_rpliprichness_UE_hr_40cells_hr
## 3 vectorruggedness_hr_ws25
## 4 geom_hr_L50m_fl1_rplipdominance_UE_hr_40cells_hr
## 5 minic_ws23_hr_hr
## 6 Vertical_Distance_to_Channel_Network_50m
## 7 geom_hr_L50m_fl1_rplipmps_UE_hr_10cells_hr
## 8 longc_ws11_10m
## 9 geom_hr_L3_fl10_rplipmps_UE_hr_10cells_hr
## 10 geom_hr_L3_fl10_rplipdominance_UE_hr_5cells_hr
## [1] "10fold cv-error: 0.601851851851852"
## [1] "For predictors geom_hr_L50m_fl10_rplipdominance_UE_hr_40cells_hr AND vectorruggedness_hr_ws23"
##
## preds 1 2 3 4 5
## 1 0 0 0 0 0
## 2 6 19 11 9 6
## 3 1 2 4 1 0
## 4 2 4 4 13 4
## 5 3 1 3 3 12
## [1] "Kappa overall = 0.27807486631016"
## [1] "Tau overall = 0.305555555555555"
## [1] "mean quality = 0.236286472148541"
## [1] "The quality is 0.236286472148541"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = NaN"
## [1] "###################### WITH PREDICTORS from the FW SELECTION ###################"
## [1] "10fold cv-error: 0.685185185185185"
## [1] "For predictors geom_hr_L50m_fl10_rplipdominance_UE_hr_40cells_hr AND vectorruggedness_hr_ws23 AND geom_hr_L50m_fl10_rpliprichness_UE_hr_40cells_hr AND geom_hr_L50m_fl1_rplipmps_UE_hr_40cells_hr AND CrossSectionalCurvature_hr AND geom_hr_L50m_fl10_rplipedgedensity_UE_hr_60cells_hr AND geom_hr_L3_fl10_rplipdominance_UE_hr_60cells_hr AND geom_hr_L3_fl10_rplipdominance_UE_hr_5cells_hr AND Total_Curvature_50m AND profc_ws11_10m AND geom_hr_L3_fl10_rpliprichness_UE_hr_60cells_hr AND minic_ws11_10m AND planc_ws5_10m AND vectorruggedness_hr_ws33 AND minic_DTM_50m_avg_ws7_50m AND slope_ws5_hr_hr AND planc_ws29_hr_hr AND maxic_ws23_hr_hr AND planc_ws23_hr_hr AND crosc_ws11_10m AND geom_hr_L50m_fl1_rpliprichness_UE_hr_60cells_hr AND crosc_DTM_50m_avg_ws3_50m AND geom_hr_L50m_fl1_rplipmps_UE_hr_20cells_hr AND geom_hr_L50m_fl1_rplipsimpson_UE_hr_40cells_hr AND maxic_ws11_10m AND geom_hr_L50m_fl1_rplipsimpson_UE_hr_60cells_hr AND Tangential_Curvature_50m AND geom_hr_L3_fl1_rplipmps_UE_hr_10cells_hr AND minic_ws15_10m AND geom_hr_L50m_fl1_rplippatchdensity_UE_hr_60cells_hr AND geom_hr_L50m_fl10_rplipsimpson_UE_hr_20cells_hr AND geom_hr_L50m_fl1_rplipshannon_UE_hr_40cells_hr AND Vertical_Distance_to_Channel_Network_50m AND profc_ws15_10m AND planc_ws11_10m AND geom_hr_L50m_fl1_rplipedgedensity_UE_hr_40cells_hr AND Relative_Slope_Position_hr AND geom_hr_L50m_fl1_rplipmps_UE_hr_10cells_hr AND Catchment_area_50m AND geom_hr_L3_fl10_rplippatchdensity_UE_hr_20cells_hr AND geom_hr_L50m_fl1_rpliprichness_UE_hr_40cells_hr AND vectorruggedness_hr_ws25 AND geom_hr_L50m_fl1_rplipdominance_UE_hr_40cells_hr AND minic_ws23_hr_hr AND longc_ws11_10m AND geom_hr_L3_fl10_rplipmps_UE_hr_10cells_hr"
##
## preds 1 2 3 4 5
## 1 5 0 0 0 0
## 2 1 21 2 3 2
## 3 1 1 16 1 0
## 4 4 4 2 21 3
## 5 1 0 2 1 17
## [1] "Kappa overall = 0.667180277349769"
## [1] "Tau overall = 0.675925925925926"
## [1] "mean quality = 0.573324283559578"
## [1] "The quality is 0.573324283559578"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = 0.68251991023537"
## [1] "######################WITH ALL PREDICTORS###################"
## [1] "10fold cv-error: 0.768518518518518"
##
## preds 1 2 3 4 5
## 1 0 0 0 0 0
## 2 6 26 18 17 7
## 3 0 0 0 0 0
## 4 6 0 3 9 13
## 5 0 0 1 0 2
## [1] "Kappa overall = 0.13531799729364"
## [1] "Tau overall = 0.178240740740741"
## [1] "mean quality = 0.125161574618096"
## [1] "The quality is 0.125161574618096"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect

## [1] "######### Cramer's V = NaN"
## [1] "1c.2 - Retention capacity for heavy precipitation events"
## [1] "Prediction error at end is: 0.305627705627706"
## [2] "Prediction error at end is: 0.306493506493506"
## [3] "Prediction error at end is: 0.324242424242424"
## [4] "Prediction error at end is: 0.324242424242424"
## [5] "Prediction error at end is: 0.315151515151515"
## [6] "Prediction error at end is: 0.314718614718615"
## [7] "Prediction error at end is: 0.305627705627706"
## [8] "Prediction error at end is: 0.305627705627706"
## [9] "Prediction error at end is: 0.305627705627706"
## [10] "Prediction error at end is: 0.305627705627706"
## k 1
## 1 crosc_ws7_10m
## 2 maxic_ws11_10m
## 3 Tangential_Curvature_50m
## 4 profc_ws19_hr_hr
## 5 minic_DTM_50m_avg_ws7_50m
## 6 Plan_Curvature_hr
## 7 dtm_hr_CONVEX_r10
## 8 CatchmentArea_10m
## 9 Catchment_Area2_50m
## 10 Modified_Catchment_Area_50m
## k 2 k 3
## 1 maxic_ws15_10m profc_ws11_10m
## 2 Profile_Curvature_50m Minimal_Curvature_50m
## 3 minic_ws5_10m longc_ws3_hr_hr
## 4 Total_Curvature_50m profc_ws3_hr_hr
## 5 longc_ws15_hr_hr crosc_ws11_10m
## 6 geom_hr_L3_fl1_rplipedgedensity_UE_hr_5cells_hr Profile_Curvature_hr
## 7 geom_hr_L50m_fl1_rplipdominance_UE_hr_40cells_hr maxic_ws11_10m
## 8 Vertical_Distance_to_Channel_Network_50m Convergence_Index_50m
## 9 terraintexture_hr_ws45_tp5 geom_10m_fl2_L8
## 10 Minimal_Curvature_hr Convexity_50m
## k 4
## 1 Minimal_Curvature_50m
## 2 minic_ws11_hr_hr
## 3 crosc_ws11_10m
## 4 geom_hr_L50m_fl1_rplipmps_UE_hr_5cells_hr
## 5 minic_ws13_hr_hr
## 6 geom_hr_L50m_fl10_rplipsimpson_UE_hr_10cells_hr
## 7 minic_ws5_10m
## 8 Minimal_Curvature_hr
## 9 longc_ws15_hr_hr
## 10 planc_DTM_50m_avg_ws3_50m
## k 5
## 1 longc_ws11_10m
## 2 profc_ws11_10m
## 3 Minimal_Curvature_50m
## 4 geom_hr_L3_fl10_rpliprichness_UE_hr_5cells_hr
## 5 geom_hr_L50m_fl10_rplipsimpson_UE_hr_10cells_hr
## 6 profc_ws5_10m
## 7 minic_ws5_10m
## 8 geom_hr_L3_fl10_rplipshannon_UE_hr_20cells_hr
## 9 geom_hr_L50m_fl10_rplipmps_UE_hr_5cells_hr
## 10 geom_hr_L50m_fl10_rplipshannon_UE_hr_5cells_hr
## [1] "10fold cv-error: 0.259259259259259"
## [1] "For predictors crosc_ws7_10m AND maxic_ws11_10m"
##
## preds 1 2 3 4 5
## 1 75 10 6 3 8
## 2 0 1 0 0 0
## 3 0 0 0 0 0
## 4 0 0 0 5 0
## 5 0 0 0 0 0
## [1] "Kappa overall = 0.264193792581378"
## [1] "Tau overall = 0.6875"
## [1] "mean quality = 0.29024064171123"
## [1] "The quality is 0.29024064171123"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = NaN"
## [1] "###################### WITH PREDICTORS from the FW SELECTION ###################"
## [1] "10fold cv-error: 0.259259259259259"
## [1] "For predictors crosc_ws7_10m AND maxic_ws11_10m AND Tangential_Curvature_50m AND profc_ws19_hr_hr AND minic_DTM_50m_avg_ws7_50m AND Plan_Curvature_hr AND dtm_hr_CONVEX_r10 AND CatchmentArea_10m AND Catchment_Area2_50m AND Modified_Catchment_Area_50m AND maxic_ws15_10m AND Profile_Curvature_50m AND minic_ws5_10m AND Total_Curvature_50m AND longc_ws15_hr_hr AND geom_hr_L3_fl1_rplipedgedensity_UE_hr_5cells_hr AND geom_hr_L50m_fl1_rplipdominance_UE_hr_40cells_hr AND Vertical_Distance_to_Channel_Network_50m AND terraintexture_hr_ws45_tp5 AND Minimal_Curvature_hr AND profc_ws11_10m AND Minimal_Curvature_50m AND longc_ws3_hr_hr AND profc_ws3_hr_hr AND crosc_ws11_10m AND Profile_Curvature_hr AND Convergence_Index_50m AND geom_10m_fl2_L8 AND Convexity_50m AND minic_ws11_hr_hr AND geom_hr_L50m_fl1_rplipmps_UE_hr_5cells_hr AND minic_ws13_hr_hr AND geom_hr_L50m_fl10_rplipsimpson_UE_hr_10cells_hr AND planc_DTM_50m_avg_ws3_50m AND longc_ws11_10m AND geom_hr_L3_fl10_rpliprichness_UE_hr_5cells_hr AND profc_ws5_10m AND geom_hr_L3_fl10_rplipshannon_UE_hr_20cells_hr AND geom_hr_L50m_fl10_rplipmps_UE_hr_5cells_hr AND geom_hr_L50m_fl10_rplipshannon_UE_hr_5cells_hr"
##
## preds 1 2 3 4 5
## 1 75 11 6 1 6
## 2 0 0 0 0 0
## 3 0 0 0 0 0
## 4 0 0 0 7 0
## 5 0 0 0 0 2
## [1] "Kappa overall = 0.377969762419006"
## [1] "Tau overall = 0.722222222222222"
## [1] "mean quality = 0.376515151515152"
## [1] "The quality is 0.376515151515152"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = NaN"
## [1] "######################WITH ALL PREDICTORS###################"
## [1] "10fold cv-error: 0.305555555555556"
##
## preds 1 2 3 4 5
## 1 75 11 6 8 8
## 2 0 0 0 0 0
## 3 0 0 0 0 0
## 4 0 0 0 0 0
## 5 0 0 0 0 0
## [1] "Kappa overall = 0"
## [1] "Tau overall = 0.618055555555555"
## [1] "mean quality = 0.138888888888889"
## [1] "The quality is 0.138888888888889"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect

## [1] "######### Cramer's V = NaN"
## [1] "1c.3 - groundwater reformation rate"
## [1] "Prediction error at end is: 0.637662337662338"
## [2] "Prediction error at end is: 0.647186147186147"
## [3] "Prediction error at end is: 0.665367965367965"
## [4] "Prediction error at end is: 0.646320346320346"
## [5] "Prediction error at end is: 0.60995670995671"
## [6] "Prediction error at end is: 0.609523809523809"
## [7] "Prediction error at end is: 0.637229437229437"
## [8] "Prediction error at end is: 0.638095238095238"
## [9] "Prediction error at end is: 0.647186147186147"
## [10] "Prediction error at end is: 0.656709956709957"
## k 1
## 1 crosc_ws13_hr_hr
## 2 crosc_ws3_10m
## 3 terraintexture_hr_ws25_tp25
## 4 dtm_hr_TEXTURE_r5
## 5 geom_hr_L50m_fl1_rplipdominance_UE_hr_10cells_hr
## 6 Vertical_Distance_to_Channel_Network_50m
## 7 geom_hr_L3_fl1_rplippatchdensity_UE_hr_20cells_hr
## 8 geom_hr_L50m_fl1_rplipmps_UE_hr_40cells_hr
## 9 geom_hr_L3_fl10_rplippatchdensity_UE_hr_20cells_hr
## 10 geom_10m_fl8_L6
## k 2
## 1 LongitudinalCurvature_10m
## 2 geom_hr_L3_fl10_rplipmps_UE_hr_40cells_hr
## 3 Vertical_Distance_to_Channel_Network_50m
## 4 minic_ws3_hr_hr
## 5 geom_hr_L50m_fl10_rplipdominance_UE_hr_60cells_hr
## 6 minic_ws19_hr_hr
## 7 geom_hr_L50m_fl1_rplipmps_UE_hr_20cells_hr
## 8 geom_hr_L3_fl10_rplipmps_UE_hr_10cells_hr
## 9 Maximal_Curvature_50m
## 10 geom_hr_L50m_fl1_rplipmps_UE_hr_40cells_hr
## k 3
## 1 crosc_ws5_10m
## 2 geom_hr_L50m_fl10_rplippatchdensity_UE_hr_40cells_hr
## 3 geom_hr_L50m_fl1_rplipmps_UE_hr_60cells_hr
## 4 crosc_ws7_10m
## 5 Channel_Network_Base_Level_hr
## 6 planc_DTM_50m_avg_ws9_50m
## 7 planc_ws3_hr_hr
## 8 Flow_Line_Curvature_hr
## 9 terraintexture_hr_ws41_tp5
## 10 CrossSectionalCurvature_50m
## k 4
## 1 minic_ws15_10m
## 2 Longitudinal_Curvature_hr
## 3 elev_ws15_10m
## 4 terraintexture_hr_ws37_tp25
## 5 crosc_ws5_10m
## 6 geom_hr_L3_fl1_rplipmps_UE_hr_10cells_hr
## 7 Total_Curvature_50m
## 8 geom_hr_L3_fl10_rplipmps_UE_hr_40cells_hr
## 9 crosc_DTM_50m_avg_ws5_50m
## 10 geom_hr_L3_fl1_rplipmps_UE_hr_20cells_hr
## k 5
## 1 LS_Factor_hr
## 2 vectorruggedness_hr_ws53
## 3 geom_hr_L3_fl1_rplipdominance_UE_hr_10cells_hr
## 4 geom_hr_L3_fl10_rplipsimpson_UE_hr_40cells_hr
## 5 ValleyDepth_10m
## 6 Catchment_Area_hr
## 7 geom_hr_L3_fl10_rplipdominance_UE_hr_5cells_hr
## 8 geom_hr_L50m_fl10_rplipmps_UE_hr_20cells_hr
## 9 geom_hr_L50m_fl1_rplipdominance_UE_hr_10cells_hr
## 10 profc_ws7_hr_hr
## [1] "10fold cv-error: 0.564814814814815"
## [1] "For predictors crosc_ws13_hr_hr AND crosc_ws3_10m"
##
## preds 1 2 3 4 5
## 1 0 0 0 0 0
## 2 12 38 13 10 11
## 3 0 0 1 0 0
## 4 0 0 0 3 1
## 5 2 1 0 6 10
## [1] "Kappa overall = 0.23248730964467"
## [1] "Tau overall = 0.351851851851852"
## [1] "mean quality = 0.198213608023855"
## [1] "The quality is 0.198213608023855"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = NaN"
## [1] "###################### WITH PREDICTORS from the FW SELECTION ###################"
## [1] "10fold cv-error: 0.583333333333333"
## [1] "For predictors crosc_ws13_hr_hr AND crosc_ws3_10m AND terraintexture_hr_ws25_tp25 AND dtm_hr_TEXTURE_r5 AND geom_hr_L50m_fl1_rplipdominance_UE_hr_10cells_hr AND Vertical_Distance_to_Channel_Network_50m AND geom_hr_L3_fl1_rplippatchdensity_UE_hr_20cells_hr AND geom_hr_L50m_fl1_rplipmps_UE_hr_40cells_hr AND geom_hr_L3_fl10_rplippatchdensity_UE_hr_20cells_hr AND geom_10m_fl8_L6 AND LongitudinalCurvature_10m AND geom_hr_L3_fl10_rplipmps_UE_hr_40cells_hr AND minic_ws3_hr_hr AND geom_hr_L50m_fl10_rplipdominance_UE_hr_60cells_hr AND minic_ws19_hr_hr AND geom_hr_L50m_fl1_rplipmps_UE_hr_20cells_hr AND geom_hr_L3_fl10_rplipmps_UE_hr_10cells_hr AND Maximal_Curvature_50m AND crosc_ws5_10m AND geom_hr_L50m_fl10_rplippatchdensity_UE_hr_40cells_hr AND geom_hr_L50m_fl1_rplipmps_UE_hr_60cells_hr AND crosc_ws7_10m AND Channel_Network_Base_Level_hr AND planc_DTM_50m_avg_ws9_50m AND planc_ws3_hr_hr AND Flow_Line_Curvature_hr AND terraintexture_hr_ws41_tp5 AND CrossSectionalCurvature_50m AND minic_ws15_10m AND Longitudinal_Curvature_hr AND elev_ws15_10m AND terraintexture_hr_ws37_tp25 AND geom_hr_L3_fl1_rplipmps_UE_hr_10cells_hr AND Total_Curvature_50m AND crosc_DTM_50m_avg_ws5_50m AND geom_hr_L3_fl1_rplipmps_UE_hr_20cells_hr AND LS_Factor_hr AND vectorruggedness_hr_ws53 AND geom_hr_L3_fl1_rplipdominance_UE_hr_10cells_hr AND geom_hr_L3_fl10_rplipsimpson_UE_hr_40cells_hr AND ValleyDepth_10m AND Catchment_Area_hr AND geom_hr_L3_fl10_rplipdominance_UE_hr_5cells_hr AND geom_hr_L50m_fl10_rplipmps_UE_hr_20cells_hr AND profc_ws7_hr_hr"
##
## preds 1 2 3 4 5
## 1 6 0 0 0 0
## 2 8 39 7 4 7
## 3 0 0 4 0 0
## 4 0 0 2 15 0
## 5 0 0 1 0 15
## [1] "Kappa overall = 0.623286023574693"
## [1] "Tau overall = 0.664351851851852"
## [1] "mean quality = 0.536149068322981"
## [1] "The quality is 0.536149068322981"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = 0.678740141625793"
## [1] "######################WITH ALL PREDICTORS###################"
## [1] "10fold cv-error: 0.62037037037037"
##
## preds 1 2 3 4 5
## 1 0 0 0 0 0
## 2 12 38 14 16 14
## 3 0 0 0 0 0
## 4 0 0 0 2 0
## 5 2 1 0 1 8
## [1] "Kappa overall = 0.158004158004158"
## [1] "Tau overall = 0.305555555555555"
## [1] "mean quality = 0.162591093117409"
## [1] "The quality is 0.162591093117409"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect

## [1] "######### Cramer's V = NaN"
## [1] "1c.4 - Potential for providing nutrients for plants"
## [1] "Prediction error at end is: 0.333766233766234"
## [2] "Prediction error at end is: 0.269264069264069"
## [3] "Prediction error at end is: 0.268398268398268"
## [4] "Prediction error at end is: 0.25021645021645"
## [5] "Prediction error at end is: 0.277922077922078"
## [6] "Prediction error at end is: 0.286147186147186"
## [7] "Prediction error at end is: 0.231168831168831"
## [8] "Prediction error at end is: 0.213419913419913"
## [9] "Prediction error at end is: 0.203896103896104"
## [10] "Prediction error at end is: 0.213419913419913"
## k 1
## 1 minic_ws9_hr_hr
## 2 Vertical_Distance_to_Channel_Network_50m
## 3 ValleyDepth_10m
## 4 geom_10m_fl10_L13
## 5 geom_hr_L3_fl10_rpliprichness_UE_hr_5cells_hr
## 6 geom_hr_L3_fl10_rplipsimpson_UE_hr_40cells_hr
## 7 geom_hr_L3_fl1_rplipmps_UE_hr_5cells_hr
## 8 SGUcode_vectorruggedness_hr_ws57_TRI_hr_ws31
## 9 geom_hr_L50m_fl10_rplipdominance_UE_hr_5cells_hr
## 10 planc_DTM_50m_avg_ws7_50m
## k 2
## 1 minic_ws5_hr_hr
## 2 crosc_DTM_50m_avg_ws5_50m
## 3 geom_hr_L50m_fl10_rplipdominance_UE_hr_5cells_hr
## 4 maxic_ws3_hr_hr
## 5 geom_hr_L3_fl10_rpliprichness_UE_hr_40cells_hr
## 6 planc_ws5_hr_hr
## 7 geom_hr_L3_fl10_rplipshannon_UE_hr_40cells_hr
## 8 geom_hr_L50m_fl1_rplippatchdensity_UE_hr_20cells_hr
## 9 Normalized_Height_50m
## 10 geom_hr_L3_fl1_rplipdominance_UE_hr_60cells_hr
## k 3
## 1 SGU
## 2 geom_hr_L3_fl10_rplippatchdensity_UE_hr_40cells_hr
## 3 ValleyDepth_hr
## 4 crosc_ws29_hr_hr
## 5 Total_Curvature_hr
## 6 geom_hr_L50m_fl1_rplipmps_UE_hr_20cells_hr
## 7 Mid_Slope_Positon_50m
## 8 Topographic_Wetness_Index_50m
## 9 geom_hr_L50m_fl10_rpliprichness_UE_hr_60cells_hr
## 10 terraintexture_hr_ws25_tp25
## k 4
## 1 SGU
## 2 ValleyDepth_hr
## 3 geom_hr_L3_fl10_rplippatchdensity_UE_hr_40cells_hr
## 4 geom_hr_L3_fl1_rplippatchdensity_UE_hr_5cells_hr
## 5 TRI_hr_ws1
## 6 ValleyDepth_10m
## 7 Modified_Catchment_Area_50m
## 8 geom_hr_L50m_fl1_rplipshannon_UE_hr_60cells_hr
## 9 fischerk_ws23_hr
## 10 dtm_hr_TEXTURE_r5
## k 5
## 1 SGU
## 2 Vertical_Distance_to_Channel_Network_50m
## 3 ValleyDepth_10m
## 4 Profile_Curvature_hr
## 5 geom_hr_L3_fl10_rpliprichness_UE_hr_5cells_hr
## 6 geom_hr_L50m_fl1_rplipmps_UE_hr_10cells_hr
## 7 Modified_Catchment_Area_50m
## 8 geom_hr_L50m_fl1_rplipdominance_UE_hr_5cells_hr
## 9 crosc_ws3_hr_hr
## 10 Topographic_Wetness_Index_50m
## [1] "10fold cv-error: 0.277777777777778"
## [1] "For predictors minic_ws9_hr_hr AND Vertical_Distance_to_Channel_Network_50m"
##
## preds 1 3 5
## 1 58 5 8
## 3 0 0 0
## 5 7 6 24
## [1] "Kappa overall = 0.521227621483376"
## [1] "Tau overall = 0.638888888888889"
## [1] "mean quality = 0.425641025641026"
## [1] "The quality is 0.425641025641026"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = NaN"
## [1] "###################### WITH PREDICTORS from the FW SELECTION ###################"
## [1] "10fold cv-error: 0.194444444444444"
## [1] "For predictors minic_ws9_hr_hr AND Vertical_Distance_to_Channel_Network_50m AND ValleyDepth_10m AND geom_10m_fl10_L13 AND geom_hr_L3_fl10_rpliprichness_UE_hr_5cells_hr AND geom_hr_L3_fl10_rplipsimpson_UE_hr_40cells_hr AND geom_hr_L3_fl1_rplipmps_UE_hr_5cells_hr AND SGUcode_vectorruggedness_hr_ws57_TRI_hr_ws31 AND geom_hr_L50m_fl10_rplipdominance_UE_hr_5cells_hr AND planc_DTM_50m_avg_ws7_50m AND minic_ws5_hr_hr AND crosc_DTM_50m_avg_ws5_50m AND maxic_ws3_hr_hr AND geom_hr_L3_fl10_rpliprichness_UE_hr_40cells_hr AND planc_ws5_hr_hr AND geom_hr_L3_fl10_rplipshannon_UE_hr_40cells_hr AND geom_hr_L50m_fl1_rplippatchdensity_UE_hr_20cells_hr AND Normalized_Height_50m AND geom_hr_L3_fl1_rplipdominance_UE_hr_60cells_hr AND SGU AND geom_hr_L3_fl10_rplippatchdensity_UE_hr_40cells_hr AND ValleyDepth_hr AND crosc_ws29_hr_hr AND Total_Curvature_hr AND geom_hr_L50m_fl1_rplipmps_UE_hr_20cells_hr AND Mid_Slope_Positon_50m AND Topographic_Wetness_Index_50m AND geom_hr_L50m_fl10_rpliprichness_UE_hr_60cells_hr AND terraintexture_hr_ws25_tp25 AND geom_hr_L3_fl1_rplippatchdensity_UE_hr_5cells_hr AND TRI_hr_ws1 AND Modified_Catchment_Area_50m AND geom_hr_L50m_fl1_rplipshannon_UE_hr_60cells_hr AND fischerk_ws23_hr AND dtm_hr_TEXTURE_r5 AND Profile_Curvature_hr AND geom_hr_L50m_fl1_rplipmps_UE_hr_10cells_hr AND geom_hr_L50m_fl1_rplipdominance_UE_hr_5cells_hr AND crosc_ws3_hr_hr"
##
## preds 1 3 5
## 1 64 7 1
## 3 0 0 0
## 5 1 4 31
## [1] "Kappa overall = 0.759259259259259"
## [1] "Tau overall = 0.819444444444444"
## [1] "mean quality = 0.571516722201654"
## [1] "The quality is 0.571516722201654"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = NaN"
## [1] "######################WITH ALL PREDICTORS###################"
## [1] "10fold cv-error: 0.425925925925926"
##
## preds 1 3 5
## 1 65 11 23
## 3 0 0 0
## 5 0 0 9
## [1] "Kappa overall = 0.256830601092896"
## [1] "Tau overall = 0.527777777777778"
## [1] "mean quality = 0.312605218855219"
## [1] "The quality is 0.312605218855219"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect

## [1] "######### Cramer's V = NaN"
## [1] "1c.5 - Potential as a CO2 sink"
## [1] "Prediction error at end is: 0.325108225108225"
## [2] "Prediction error at end is: 0.335064935064935"
## [3] "Prediction error at end is: 0.287878787878788"
## [4] "Prediction error at end is: 0.278787878787879"
## [5] "Prediction error at end is: 0.296969696969697"
## [6] "Prediction error at end is: 0.278354978354978"
## [7] "Prediction error at end is: 0.269264069264069"
## [8] "Prediction error at end is: 0.306060606060606"
## [9] "Prediction error at end is: 0.325108225108225"
## [10] "Prediction error at end is: 0.297402597402597"
## k 1
## 1 Channel_Network_Base_Level_hr
## 2 crosc_ws11_hr_hr
## 3 Topographic_Wetness_Index_50m
## 4 Catchment_area_50m
## 5 vectorruggedness_hr_ws11
## 6 terraintexture_hr_ws13_tp25
## 7 ValleyDepth_hr
## 8 Catchment_Area_hr
## 9 crosc_DTM_50m_avg_ws9_50m
## 10 Catchment_Area2_50m
## k 2
## 1 elev_ws11_10m
## 2 maxic_ws3_hr_hr
## 3 maxic_ws15_hr_hr
## 4 MaximalCurvature_10m
## 5 ValleyDepth_10m
## 6 Mid_Slope_Positon_50m
## 7 vectorruggedness_hr_ws5
## 8 geom_hr_L50m_fl10_rpliprichness_UE_hr_20cells_hr
## 9 slope_DTM_50m_avg_ws5_50m
## 10 planc_DTM_50m_avg_ws9_50m
## k 3
## 1 elev_ws11_10m
## 2 Catchment_area_50m
## 3 MaximalCurvature_10m
## 4 terraintexture_hr_ws57_tp25
## 5 Vertical_Distance_to_Channel_Network_hr
## 6 planc_DTM_50m_avg_ws9_50m
## 7 profc_DTM_50m_avg_ws7_50m
## 8 planc_ws15_hr_hr
## 9 planc_ws19_hr_hr
## 10 vectorruggedness_hr_ws3
## k 4
## 1 elev_ws11_10m
## 2 Catchment_slope_50m
## 3 LSFactor_10m
## 4 slope_DTM_50m_avg_ws7_50m
## 5 ChannelNetworkBaseLevel_10m
## 6 Valley_Depth_hr
## 7 geom_hr_L3_fl10_rplipdominance_UE_hr_5cells_hr
## 8 longc_DTM_50m_avg_ws5_50m
## 9 geom_hr_L3_fl1_rpliprichness_UE_hr_60cells_hr
## 10 minic_ws15_10m
## k 5
## 1 Channel_Network_Base_Level_hr
## 2 Valley_Depth_hr
## 3 slope_DTM_50m_avg_ws5_50m
## 4 Catchment_area_50m
## 5 crosc_ws13_hr_hr
## 6 planc_DTM_50m_avg_ws9_50m
## 7 geom_hr_L3_fl10_rplipdominance_UE_hr_60cells_hr
## 8 maxic_DTM_50m_avg_ws7_50m
## 9 longc_ws3_10m
## 10 ValleyDepth_10m
## [1] "10fold cv-error: 0.296296296296296"
## [1] "For predictors Channel_Network_Base_Level_hr AND crosc_ws11_hr_hr"
##
## preds 1 2 3 4 5
## 1 44 0 6 1 0
## 2 0 0 0 0 0
## 3 0 0 0 0 0
## 4 7 1 12 32 5
## 5 0 0 0 0 0
## [1] "Kappa overall = 0.518796992481203"
## [1] "Tau overall = 0.62962962962963"
## [1] "mean quality = 0.262068965517241"
## [1] "The quality is 0.262068965517241"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = NaN"
## [1] "###################### WITH PREDICTORS from the FW SELECTION ###################"
## [1] "10fold cv-error: 0.268518518518518"
## [1] "For predictors Channel_Network_Base_Level_hr AND crosc_ws11_hr_hr AND Topographic_Wetness_Index_50m AND Catchment_area_50m AND vectorruggedness_hr_ws11 AND terraintexture_hr_ws13_tp25 AND ValleyDepth_hr AND Catchment_Area_hr AND crosc_DTM_50m_avg_ws9_50m AND Catchment_Area2_50m AND elev_ws11_10m AND maxic_ws3_hr_hr AND maxic_ws15_hr_hr AND MaximalCurvature_10m AND ValleyDepth_10m AND Mid_Slope_Positon_50m AND vectorruggedness_hr_ws5 AND geom_hr_L50m_fl10_rpliprichness_UE_hr_20cells_hr AND slope_DTM_50m_avg_ws5_50m AND planc_DTM_50m_avg_ws9_50m AND terraintexture_hr_ws57_tp25 AND Vertical_Distance_to_Channel_Network_hr AND profc_DTM_50m_avg_ws7_50m AND planc_ws15_hr_hr AND planc_ws19_hr_hr AND vectorruggedness_hr_ws3 AND Catchment_slope_50m AND LSFactor_10m AND slope_DTM_50m_avg_ws7_50m AND ChannelNetworkBaseLevel_10m AND Valley_Depth_hr AND geom_hr_L3_fl10_rplipdominance_UE_hr_5cells_hr AND longc_DTM_50m_avg_ws5_50m AND geom_hr_L3_fl1_rpliprichness_UE_hr_60cells_hr AND minic_ws15_10m AND crosc_ws13_hr_hr AND geom_hr_L3_fl10_rplipdominance_UE_hr_60cells_hr AND maxic_DTM_50m_avg_ws7_50m AND longc_ws3_10m"
##
## preds 1 2 3 4 5
## 1 49 0 1 0 1
## 2 0 1 0 0 0
## 3 1 0 14 2 1
## 4 1 0 3 31 3
## 5 0 0 0 0 0
## [1] "Kappa overall = 0.812399786210583"
## [1] "Tau overall = 0.849537037037037"
## [1] "mean quality = 0.667178387650086"
## [1] "The quality is 0.667178387650086"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = NaN"
## [1] "######################WITH ALL PREDICTORS###################"
## [1] "10fold cv-error: 0.416666666666667"
##
## preds 1 2 3 4 5
## 1 47 0 6 7 2
## 2 0 0 0 0 0
## 3 0 0 0 0 0
## 4 4 1 12 26 3
## 5 0 0 0 0 0
## [1] "Kappa overall = 0.458762886597938"
## [1] "Tau overall = 0.594907407407407"
## [1] "mean quality = 0.240537449971412"
## [1] "The quality is 0.240537449971412"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect

## [1] "######### Cramer's V = NaN"
## [1] "1d.1 - Potential for retention of heavy metals"
## [1] "Prediction error at end is: 0.417748917748918"
## [2] "Prediction error at end is: 0.380519480519481"
## [3] "Prediction error at end is: 0.38008658008658"
## [4] "Prediction error at end is: 0.38008658008658"
## [5] "Prediction error at end is: 0.388311688311688"
## [6] "Prediction error at end is: 0.351515151515152"
## [7] "Prediction error at end is: 0.37012987012987"
## [8] "Prediction error at end is: 0.351082251082251"
## [9] "Prediction error at end is: 0.36017316017316"
## [10] "Prediction error at end is: 0.36969696969697"
## k 1 k 2
## 1 vectorruggedness_hr_ws47 vectorruggedness_hr_ws31
## 2 dtm_hr_CONVEX_r30 minic_ws5_hr_hr
## 3 TWI_10m terraintexture_hr_ws45_tp25
## 4 Topographic_Wetness_Index_50m Standardized_Height_50m
## 5 profc_ws3_hr_hr planc_DTM_50m_avg_ws11_50m
## 6 minic_DTM_50m_avg_ws9_50m dtm_hr_CONVEX_r30
## 7 dtm_hr_TEXTURE_r20 Tangential_Curvature_50m
## 8 geom_hr_L50m_fl10_rplipmps_UE_hr_40cells_hr NormalizedHeight_10m
## 9 geom_hr_L50m_fl1_rplipmps_UE_hr_60cells_hr vectorruggedness_hr_ws55
## 10 Catchment_area_50m vectorruggedness_hr_ws45
## k 3
## 1 vectorruggedness_hr_ws47
## 2 minic_ws29_hr_hr
## 3 TRI_hr_ws11
## 4 geom_hr_L3_fl10_rplipmps_UE_hr_20cells_hr
## 5 geom_hr_L3_fl1_rplipshannon_UE_hr_60cells_hr
## 6 vectorruggedness_hr_ws49
## 7 geom_hr_L3_fl1_rplipdominance_UE_hr_40cells_hr
## 8 longc_ws19_hr_hr
## 9 minic_ws15_10m
## 10 maxic_ws5_10m
## k 4
## 1 TRI_hr_ws20
## 2 geom_hr_L3_fl1_rplipshannon_UE_hr_60cells_hr
## 3 Texture_10m
## 4 geom_hr_L3_fl10_rplipdominance_UE_hr_5cells_hr
## 5 dtm_hr_TEXTURE_r10
## 6 Modified_Catchment_Area_50m
## 7 geom_hr_L50m_fl1_rplipedgedensity_UE_hr_40cells_hr
## 8 dtm_hr_TEXTURE_r5
## 9 geom_hr_L3_fl1_rplipedgedensity_UE_hr_40cells_hr
## 10 geom_hr_L50m_fl1_rplipmps_UE_hr_60cells_hr
## k 5
## 1 Channel_Network_Base_Level_hr
## 2 slope_DTM_50m_avg_ws5_50m
## 3 longc_ws11_hr_hr
## 4 geom_hr_L3_fl1_rplipdominance_UE_hr_60cells_hr
## 5 longc_ws3_10m
## 6 vectorruggedness_hr_ws9
## 7 geom_hr_L3_fl10_rplipdominance_UE_hr_40cells_hr
## 8 MaximalCurvature_10m
## 9 geom_hr_L3_fl1_rplipsimpson_UE_hr_40cells_hr
## 10 Longitudinal_Curvature_hr
## [1] "10fold cv-error: 0.324074074074074"
## [1] "For predictors vectorruggedness_hr_ws47 AND dtm_hr_CONVEX_r30"
##
## preds 1 2 3 4 5
## 1 38 4 5 2 6
## 2 0 0 0 0 0
## 3 0 0 0 0 0
## 4 0 0 0 2 0
## 5 4 3 5 3 36
## [1] "Kappa overall = 0.519866629619339"
## [1] "Tau overall = 0.62962962962963"
## [1] "mean quality = 0.312272205938575"
## [1] "The quality is 0.312272205938575"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = NaN"
## [1] "###################### WITH PREDICTORS from the FW SELECTION ###################"
## [1] "10fold cv-error: 0.296296296296296"
## [1] "For predictors vectorruggedness_hr_ws47 AND dtm_hr_CONVEX_r30 AND TWI_10m AND Topographic_Wetness_Index_50m AND profc_ws3_hr_hr AND minic_DTM_50m_avg_ws9_50m AND dtm_hr_TEXTURE_r20 AND geom_hr_L50m_fl10_rplipmps_UE_hr_40cells_hr AND geom_hr_L50m_fl1_rplipmps_UE_hr_60cells_hr AND Catchment_area_50m AND vectorruggedness_hr_ws31 AND minic_ws5_hr_hr AND terraintexture_hr_ws45_tp25 AND Standardized_Height_50m AND planc_DTM_50m_avg_ws11_50m AND Tangential_Curvature_50m AND NormalizedHeight_10m AND vectorruggedness_hr_ws55 AND vectorruggedness_hr_ws45 AND minic_ws29_hr_hr AND TRI_hr_ws11 AND geom_hr_L3_fl10_rplipmps_UE_hr_20cells_hr AND geom_hr_L3_fl1_rplipshannon_UE_hr_60cells_hr AND vectorruggedness_hr_ws49 AND geom_hr_L3_fl1_rplipdominance_UE_hr_40cells_hr AND longc_ws19_hr_hr AND minic_ws15_10m AND maxic_ws5_10m AND TRI_hr_ws20 AND Texture_10m AND geom_hr_L3_fl10_rplipdominance_UE_hr_5cells_hr AND dtm_hr_TEXTURE_r10 AND Modified_Catchment_Area_50m AND geom_hr_L50m_fl1_rplipedgedensity_UE_hr_40cells_hr AND dtm_hr_TEXTURE_r5 AND geom_hr_L3_fl1_rplipedgedensity_UE_hr_40cells_hr AND Channel_Network_Base_Level_hr AND slope_DTM_50m_avg_ws5_50m AND longc_ws11_hr_hr AND geom_hr_L3_fl1_rplipdominance_UE_hr_60cells_hr AND longc_ws3_10m AND vectorruggedness_hr_ws9 AND geom_hr_L3_fl10_rplipdominance_UE_hr_40cells_hr AND MaximalCurvature_10m AND geom_hr_L3_fl1_rplipsimpson_UE_hr_40cells_hr AND Longitudinal_Curvature_hr"
##
## preds 1 2 3 4 5
## 1 42 6 5 3 3
## 2 0 0 0 0 0
## 3 0 0 3 0 0
## 4 0 0 0 2 0
## 5 0 1 2 2 39
## [1] "Kappa overall = 0.674252810529202"
## [1] "Tau overall = 0.74537037037037"
## [1] "mean quality = 0.4254731853073"
## [1] "The quality is 0.4254731853073"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = NaN"
## [1] "######################WITH ALL PREDICTORS###################"
## [1] "10fold cv-error: 0.361111111111111"
##
## preds 1 2 3 4 5
## 1 38 4 6 3 7
## 2 0 0 0 0 0
## 3 0 0 0 0 0
## 4 0 0 0 0 0
## 5 4 3 4 4 35
## [1] "Kappa overall = 0.46969696969697"
## [1] "Tau overall = 0.594907407407407"
## [1] "mean quality = 0.24538766270515"
## [1] "The quality is 0.24538766270515"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect

## [1] "######### Cramer's V = NaN"
## [1] "1d.2 - Potential for transforming organic contaminants"
## [1] "Prediction error at end is: 0.51991341991342"
## [2] "Prediction error at end is: 0.527705627705628"
## [3] "Prediction error at end is: 0.593506493506494"
## [4] "Prediction error at end is: 0.602164502164502"
## [5] "Prediction error at end is: 0.565367965367965"
## [6] "Prediction error at end is: 0.583549783549784"
## [7] "Prediction error at end is: 0.555844155844156"
## [8] "Prediction error at end is: 0.547186147186147"
## [9] "Prediction error at end is: 0.564935064935065"
## [10] "Prediction error at end is: 0.518614718614719"
## k 1
## 1 Channel_Network_Base_Level_hr
## 2 crosc_ws13_hr_hr
## 3 geom_hr_L50m_fl10_rplipdominance_UE_hr_40cells_hr
## 4 Relative_Slope_Position_hr
## 5 slope_DTM_50m_avg_ws3_50m
## 6 Vertical_Distance_to_Channel_Network_50m
## 7 geom_hr_L3_fl10_rplipdominance_UE_hr_10cells_hr
## 8 Slope_50m
## 9 Catchment_area_50m
## 10 geom_hr_L50m_fl10_rplipmps_UE_hr_10cells_hr
## k 2
## 1 Vertical_Distance_to_Channel_Network_50m
## 2 Topographic_Wetness_Index_50m
## 3 maxic_DTM_50m_avg_ws9_50m
## 4 dtm_hr_CONVEX_r20
## 5 longc_ws11_10m
## 6 General_Curvature_hr
## 7 geom_hr_L3_fl10_rplipdominance_UE_hr_10cells_hr
## 8 geom_hr_L3_fl10_rplipdominance_UE_hr_5cells_hr
## 9 geom_hr_L50m_fl10_rplipdominance_UE_hr_60cells_hr
## 10 geom_10m_fl3_L30
## k 3
## 1 elev_ws11_10m
## 2 TRI_hr_ws57
## 3 dtm_hr_CONVEX_r20
## 4 vectorruggedness_hr_ws55
## 5 Profile_Curvature_hr
## 6 Standardized_Height_hr
## 7 Texture_10m
## 8 geom_10m_fl10_L23
## 9 Standardized_Height_50m
## 10 ChannelNetworkBaseLevel_10m
## k 4
## 1 Vertical_Distance_to_Channel_Network_50m
## 2 geom_hr_L50m_fl1_rplipdominance_UE_hr_40cells_hr
## 3 elev_ws11_10m
## 4 minic_DTM_50m_avg_ws3_50m
## 5 Mid_Slope_Positon_50m
## 6 terraintexture_hr_ws45_tp25
## 7 LS_Factor_50m
## 8 longc_ws3_hr_hr
## 9 geom_hr_L3_fl10_rplippatchdensity_UE_hr_20cells_hr
## 10 Channel_Network_Base_Level_hr
## k 5
## 1 elev_ws11_10m
## 2 geom_hr_L3_fl10_rplipdominance_UE_hr_60cells_hr
## 3 geom_hr_L3_fl1_rplipdominance_UE_hr_5cells_hr
## 4 geom_hr_L3_fl1_rplipsimpson_UE_hr_5cells_hr
## 5 Channel_Network_Base_Level_hr
## 6 Convexity_50m
## 7 geom_hr_L50m_fl10_rplippatchdensity_UE_hr_20cells_hr
## 8 geom_hr_L50m_fl1_rplipedgedensity_UE_hr_5cells_hr
## 9 TRI_hr_ws36
## 10 geom_10m_fl3_L34
## [1] "10fold cv-error: 0.527777777777778"
## [1] "For predictors Channel_Network_Base_Level_hr AND crosc_ws13_hr_hr"
##
## preds 1 2 3 4 5
## 1 0 0 0 0 0
## 2 0 4 1 0 3
## 3 8 13 24 2 5
## 4 0 0 0 1 0
## 5 2 5 3 6 31
## [1] "Kappa overall = 0.367032967032967"
## [1] "Tau overall = 0.444444444444444"
## [1] "mean quality = 0.251433011433011"
## [1] "The quality is 0.251433011433011"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = NaN"
## [1] "###################### WITH PREDICTORS from the FW SELECTION ###################"
## [1] "10fold cv-error: 0.444444444444444"
## [1] "For predictors Channel_Network_Base_Level_hr AND crosc_ws13_hr_hr AND geom_hr_L50m_fl10_rplipdominance_UE_hr_40cells_hr AND Relative_Slope_Position_hr AND slope_DTM_50m_avg_ws3_50m AND Vertical_Distance_to_Channel_Network_50m AND geom_hr_L3_fl10_rplipdominance_UE_hr_10cells_hr AND Slope_50m AND Catchment_area_50m AND geom_hr_L50m_fl10_rplipmps_UE_hr_10cells_hr AND Topographic_Wetness_Index_50m AND maxic_DTM_50m_avg_ws9_50m AND dtm_hr_CONVEX_r20 AND longc_ws11_10m AND General_Curvature_hr AND geom_hr_L3_fl10_rplipdominance_UE_hr_5cells_hr AND geom_hr_L50m_fl10_rplipdominance_UE_hr_60cells_hr AND geom_10m_fl3_L30 AND elev_ws11_10m AND TRI_hr_ws57 AND vectorruggedness_hr_ws55 AND Profile_Curvature_hr AND Standardized_Height_hr AND Texture_10m AND geom_10m_fl10_L23 AND Standardized_Height_50m AND ChannelNetworkBaseLevel_10m AND geom_hr_L50m_fl1_rplipdominance_UE_hr_40cells_hr AND minic_DTM_50m_avg_ws3_50m AND Mid_Slope_Positon_50m AND terraintexture_hr_ws45_tp25 AND LS_Factor_50m AND longc_ws3_hr_hr AND geom_hr_L3_fl10_rplippatchdensity_UE_hr_20cells_hr AND geom_hr_L3_fl10_rplipdominance_UE_hr_60cells_hr AND geom_hr_L3_fl1_rplipdominance_UE_hr_5cells_hr AND geom_hr_L3_fl1_rplipsimpson_UE_hr_5cells_hr AND Convexity_50m AND geom_hr_L50m_fl10_rplippatchdensity_UE_hr_20cells_hr AND geom_hr_L50m_fl1_rplipedgedensity_UE_hr_5cells_hr AND TRI_hr_ws36 AND geom_10m_fl3_L34"
##
## preds 1 2 3 4 5
## 1 3 0 0 0 0
## 2 3 14 0 0 0
## 3 4 6 27 2 4
## 4 0 0 0 2 0
## 5 0 2 1 5 35
## [1] "Kappa overall = 0.651237890204521"
## [1] "Tau overall = 0.6875"
## [1] "mean quality = 0.488107887384483"
## [1] "The quality is 0.488107887384483"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = 0.632451537505577"
## [1] "######################WITH ALL PREDICTORS###################"
## [1] "10fold cv-error: 0.555555555555556"
##
## preds 1 2 3 4 5
## 1 0 0 0 0 0
## 2 0 0 0 0 0
## 3 6 15 18 2 3
## 4 0 0 0 0 0
## 5 4 7 10 7 36
## [1] "Kappa overall = 0.265120967741935"
## [1] "Tau overall = 0.375"
## [1] "mean quality = 0.174129353233831"
## [1] "The quality is 0.174129353233831"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect

## [1] "######### Cramer's V = NaN"
## [1] "1d.3 - Potential as filter and buffer for organic contaminants"
## [1] "Prediction error at end is: 0.0367965367965368"
## [2] "Prediction error at end is: 0.0367965367965368"
## [3] "Prediction error at end is: 0.0458874458874459"
## [4] "Prediction error at end is: 0.0367965367965368"
## [5] "Prediction error at end is: 0.0367965367965368"
## [6] "Prediction error at end is: 0.0367965367965368"
## [7] "Prediction error at end is: 0.0458874458874459"
## [8] "Prediction error at end is: 0.0458874458874459"
## [9] "Prediction error at end is: 0.0367965367965368"
## [10] "Prediction error at end is: 0.0367965367965368"
## k 1 k 2
## 1 PlanCurvature_10m crosc_ws11_10m
## 2 planc_ws11_hr_hr crosc_ws15_10m
## 3 geom_hr_L50m_fl1_rplipdominance_UE_hr_60cells_hr crosc_ws3_10m
## 4 fischerk_ws7_hr crosc_ws5_10m
## 5 vectorstrength_hr_ws7_hr crosc_ws7_10m
## 6 Convexity_10m longc_ws11_10m
## 7 Catchment_Area2_50m longc_ws15_10m
## 8 planc_ws9_hr_hr longc_ws3_10m
## 9 planc_ws13_hr_hr longc_ws5_10m
## 10 fischerk_ws3_hr longc_ws7_10m
## k 3
## 1 PlanCurvature_10m
## 2 geom_hr_L50m_fl1_rplippatchdensity_UE_hr_20cells_hr
## 3 geom_hr_L50m_fl1_rplippatchnum_UE_hr_20cells_hr
## 4 planc_ws11_hr_hr
## 5 geom_hr_L50m_fl1_rplipedgedensity_UE_hr_40cells_hr
## 6 geom_hr_L50m_fl1_rplippatchdensity_UE_hr_40cells_hr
## 7 geom_hr_L50m_fl1_rplippatchnum_UE_hr_40cells_hr
## 8 geom_hr_L50m_fl1_rplipshape_UE_hr_40cells_hr
## 9 fischerk_ws7_hr
## 10 vectorstrength_hr_ws7_hr
## k 4 k 5
## 1 PlanCurvature_10m crosc_ws11_10m
## 2 crosc_ws11_10m crosc_ws15_10m
## 3 fischerk_ws7_hr crosc_ws3_10m
## 4 vectorstrength_hr_ws7_hr crosc_ws5_10m
## 5 Convexity_10m crosc_ws7_10m
## 6 planc_ws13_hr_hr longc_ws11_10m
## 7 Catchment_Area2_50m longc_ws15_10m
## 8 geom_hr_L3_fl10_rplipdominance_UE_hr_60cells_hr longc_ws3_10m
## 9 planc_ws9_hr_hr longc_ws5_10m
## 10 planc_ws5_hr_hr longc_ws7_10m
## [1] "10fold cv-error: 0.0185185185185185"
## [1] "For predictors PlanCurvature_10m AND planc_ws11_hr_hr"
##
## preds 4 5
## 4 2 0
## 5 2 104
## [1] "Kappa overall = 0.658227848101266"
## [1] "Tau overall = 0.962962962962963"
## [1] "mean quality = 0.740566037735849"
## [1] "The quality is 0.740566037735849"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = 0.518568491248852"
## [1] "###################### WITH PREDICTORS from the FW SELECTION ###################"
## [1] "10fold cv-error: 0.0370370370370371"
## [1] "For predictors PlanCurvature_10m AND planc_ws11_hr_hr AND geom_hr_L50m_fl1_rplipdominance_UE_hr_60cells_hr AND fischerk_ws7_hr AND vectorstrength_hr_ws7_hr AND Convexity_10m AND Catchment_Area2_50m AND planc_ws9_hr_hr AND planc_ws13_hr_hr AND fischerk_ws3_hr AND crosc_ws11_10m AND crosc_ws15_10m AND crosc_ws3_10m AND crosc_ws5_10m AND crosc_ws7_10m AND longc_ws11_10m AND longc_ws15_10m AND longc_ws3_10m AND longc_ws5_10m AND longc_ws7_10m AND geom_hr_L50m_fl1_rplippatchdensity_UE_hr_20cells_hr AND geom_hr_L50m_fl1_rplippatchnum_UE_hr_20cells_hr AND geom_hr_L50m_fl1_rplipedgedensity_UE_hr_40cells_hr AND geom_hr_L50m_fl1_rplippatchdensity_UE_hr_40cells_hr AND geom_hr_L50m_fl1_rplippatchnum_UE_hr_40cells_hr AND geom_hr_L50m_fl1_rplipshape_UE_hr_40cells_hr AND geom_hr_L3_fl10_rplipdominance_UE_hr_60cells_hr AND planc_ws5_hr_hr"
##
## preds 4 5
## 4 3 0
## 5 1 104
## [1] "Kappa overall = 0.852459016393442"
## [1] "Tau overall = 0.981481481481481"
## [1] "mean quality = 0.870238095238095"
## [1] "The quality is 0.870238095238095"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = 0.712718059941681"
## [1] "######################WITH ALL PREDICTORS###################"
## [1] "10fold cv-error: 0.0370370370370371"
##
## preds 4 5
## 4 0 0
## 5 4 104
## [1] "Kappa overall = 0"
## [1] "Tau overall = 0.925925925925926"
## [1] "mean quality = 0.481481481481482"
## [1] "The quality is 0.481481481481482"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect

## [1] "######### Cramer's V = NaN"
## [1] "1d.4 - Potential for retention of water-soluble contaminants"
## [1] "Prediction error at end is: 0.592207792207792"
## [2] "Prediction error at end is: 0.555411255411255"
## [3] "Prediction error at end is: 0.564502164502165"
## [4] "Prediction error at end is: 0.601731601731602"
## [5] "Prediction error at end is: 0.601731601731602"
## [6] "Prediction error at end is: 0.592640692640693"
## [7] "Prediction error at end is: 0.573593073593074"
## [8] "Prediction error at end is: 0.564502164502165"
## [9] "Prediction error at end is: 0.564502164502165"
## [10] "Prediction error at end is: 0.573593073593074"
## k 1
## 1 TRI_hr_ws29
## 2 fischerk_ws55_hr
## 3 geom_hr_L3_fl1_rplipshannon_UE_hr_10cells_hr
## 4 geom_hr_L50m_fl1_rplipshannon_UE_hr_40cells_hr
## 5 slope_DTM_50m_avg_ws5_50m
## 6 Normalized_Height_50m
## 7 geom_hr_L50m_fl10_rpliprichness_UE_hr_40cells_hr
## 8 geom_hr_L50m_fl10_rpliprichness_UE_hr_60cells_hr
## 9 Catchment_area_50m
## 10 Profile_Curvature_hr
## k 2
## 1 FlowLineCurvature_10m
## 2 slope_ws11_hr_hr
## 3 geom_hr_L3_fl1_rplipsimpson_UE_hr_10cells_hr
## 4 RelativeSlopePosition_10m
## 5 crosc_ws7_hr_hr
## 6 TRI_hr_ws10
## 7 minic_ws7_10m
## 8 planc_ws13_hr_hr
## 9 geom_hr_L50m_fl10_rplipmps_UE_hr_60cells_hr
## 10 geom_10m_fl1_L17
## k 3
## 1 crosc_ws7_10m
## 2 terraintexture_hr_ws49_tp25
## 3 terraintexture_hr_ws41_tp25
## 4 Profile_Curvature_hr
## 5 maxic_ws13_hr_hr
## 6 planc_DTM_50m_avg_ws11_50m
## 7 vectorruggedness_hr_ws59
## 8 geom_hr_L3_fl1_rplipshannon_UE_hr_40cells_hr
## 9 geom_hr_L50m_fl1_rpliprichness_UE_hr_40cells_hr
## 10 Convexity_10m
## k 4
## 1 maxic_ws7_10m
## 2 sagaTopographic_Wetness_Index_50m
## 3 geom_hr_L3_fl1_rplipdominance_UE_hr_10cells_hr
## 4 geom_hr_L3_fl1_rplipshannon_UE_hr_20cells_hr
## 5 geom_hr_L3_fl1_rpliprichness_UE_hr_40cells_hr
## 6 geom_hr_L50m_fl1_rplippatchdensity_UE_hr_20cells_hr
## 7 Mass_Balance_Index_hr
## 8 geom_hr_L50m_fl10_rplipmps_UE_hr_20cells_hr
## 9 geom_hr_L3_fl1_rplipshannon_UE_hr_40cells_hr
## 10 geom_hr_L3_fl1_rplipsimpson_UE_hr_60cells_hr
## k 5
## 1 TRI_hr_ws44
## 2 slope_ws5_hr_hr
## 3 Tangential_Curvature_hr
## 4 geom_hr_L50m_fl10_rplippatchdensity_UE_hr_5cells_hr
## 5 Profile_Curvature_50m
## 6 planc_DTM_50m_avg_ws11_50m
## 7 LongitudinalCurvature_10m
## 8 geom_hr_L50m_fl1_rplipmps_UE_hr_20cells_hr
## 9 geom_hr_L50m_fl1_rplipdominance_UE_hr_5cells_hr
## 10 Vertical_Distance_to_Channel_Network_50m
## [1] "10fold cv-error: 0.462962962962963"
## [1] "For predictors TRI_hr_ws29 AND fischerk_ws55_hr"
##
## preds 1 2 3 4 5
## 1 45 10 7 11 1
## 2 0 0 0 0 0
## 3 2 0 7 3 3
## 4 0 4 3 8 3
## 5 0 0 0 0 1
## [1] "Kappa overall = 0.325627740135512"
## [1] "Tau overall = 0.456018518518518"
## [1] "mean quality = 0.249421052631579"
## [1] "The quality is 0.249421052631579"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = NaN"
## [1] "###################### WITH PREDICTORS from the FW SELECTION ###################"
## [1] "10fold cv-error: 0.425925925925926"
## [1] "For predictors TRI_hr_ws29 AND fischerk_ws55_hr AND geom_hr_L3_fl1_rplipshannon_UE_hr_10cells_hr AND geom_hr_L50m_fl1_rplipshannon_UE_hr_40cells_hr AND slope_DTM_50m_avg_ws5_50m AND Normalized_Height_50m AND geom_hr_L50m_fl10_rpliprichness_UE_hr_40cells_hr AND geom_hr_L50m_fl10_rpliprichness_UE_hr_60cells_hr AND Catchment_area_50m AND Profile_Curvature_hr AND FlowLineCurvature_10m AND slope_ws11_hr_hr AND geom_hr_L3_fl1_rplipsimpson_UE_hr_10cells_hr AND RelativeSlopePosition_10m AND crosc_ws7_hr_hr AND TRI_hr_ws10 AND minic_ws7_10m AND planc_ws13_hr_hr AND geom_hr_L50m_fl10_rplipmps_UE_hr_60cells_hr AND geom_10m_fl1_L17 AND crosc_ws7_10m AND terraintexture_hr_ws49_tp25 AND terraintexture_hr_ws41_tp25 AND maxic_ws13_hr_hr AND planc_DTM_50m_avg_ws11_50m AND vectorruggedness_hr_ws59 AND geom_hr_L3_fl1_rplipshannon_UE_hr_40cells_hr AND geom_hr_L50m_fl1_rpliprichness_UE_hr_40cells_hr AND Convexity_10m AND maxic_ws7_10m AND sagaTopographic_Wetness_Index_50m AND geom_hr_L3_fl1_rplipdominance_UE_hr_10cells_hr AND geom_hr_L3_fl1_rplipshannon_UE_hr_20cells_hr AND geom_hr_L3_fl1_rpliprichness_UE_hr_40cells_hr AND geom_hr_L50m_fl1_rplippatchdensity_UE_hr_20cells_hr AND Mass_Balance_Index_hr AND geom_hr_L50m_fl10_rplipmps_UE_hr_20cells_hr AND geom_hr_L3_fl1_rplipsimpson_UE_hr_60cells_hr AND TRI_hr_ws44 AND slope_ws5_hr_hr AND Tangential_Curvature_hr AND geom_hr_L50m_fl10_rplippatchdensity_UE_hr_5cells_hr AND Profile_Curvature_50m AND LongitudinalCurvature_10m AND geom_hr_L50m_fl1_rplipmps_UE_hr_20cells_hr AND geom_hr_L50m_fl1_rplipdominance_UE_hr_5cells_hr AND Vertical_Distance_to_Channel_Network_50m"
##
## preds 1 2 3 4 5
## 1 47 9 5 4 0
## 2 0 3 0 0 0
## 3 0 0 10 0 1
## 4 0 2 2 18 2
## 5 0 0 0 0 5
## [1] "Kappa overall = 0.654377880184332"
## [1] "Tau overall = 0.710648148148148"
## [1] "mean quality = 0.552155067155067"
## [1] "The quality is 0.552155067155067"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = 0.686929444529617"
## [1] "######################WITH ALL PREDICTORS###################"
## [1] "10fold cv-error: 0.555555555555556"
##
## preds 1 2 3 4 5
## 1 47 12 12 15 5
## 2 0 0 0 0 0
## 3 0 0 3 0 0
## 4 0 2 2 7 3
## 5 0 0 0 0 0
## [1] "Kappa overall = 0.216277746158224"
## [1] "Tau overall = 0.409722222222222"
## [1] "mean quality = 0.186866683012728"
## [1] "The quality is 0.186866683012728"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect

## [1] "######### Cramer's V = NaN"
## [1] "1d.5 - Potential as buffer for acidic contaminants"
## [1] "Prediction error at end is: 0.61038961038961"
## [2] "Prediction error at end is: 0.592207792207792"
## [3] "Prediction error at end is: 0.611688311688312"
## [4] "Prediction error at end is: 0.612554112554113"
## [5] "Prediction error at end is: 0.592640692640693"
## [6] "Prediction error at end is: 0.647619047619048"
## [7] "Prediction error at end is: 0.601298701298701"
## [8] "Prediction error at end is: 0.638961038961039"
## [9] "Prediction error at end is: 0.638528138528139"
## [10] "Prediction error at end is: 0.574891774891775"
## k 1
## 1 Standardized_Height_50m
## 2 geom_hr_L3_fl10_rplipedgedensity_UE_hr_10cells_hr
## 3 geom_hr_L50m_fl1_rplipshannon_UE_hr_5cells_hr
## 4 geom_hr_L50m_fl1_rplipshannon_UE_hr_60cells_hr
## 5 planc_DTM_50m_avg_ws3_50m
## 6 geom_hr_L3_fl10_rplipmps_UE_hr_5cells_hr
## 7 Normalized_Height_50m
## 8 Mid_Slope_Positon_50m
## 9 Slope_Height_50m
## 10 LS_Factor_hr
## k 2
## 1 Profile_Curvature_50m
## 2 Standardized_Height_50m
## 3 ValleyDepth_10m
## 4 Texture_10m
## 5 geom_hr_L3_fl1_rplipmps_UE_hr_20cells_hr
## 6 geom_hr_L3_fl10_rplippatchdensity_UE_hr_40cells_hr
## 7 longc_ws11_10m
## 8 Texture_50m
## 9 terraintexture_hr_ws41_tp25
## 10 fischerk_ws33_hr
## k 3
## 1 Catchment_slope_50m
## 2 Convexity_50m
## 3 geom_hr_L3_fl10_rplipedgedensity_UE_hr_10cells_hr
## 4 sagaTopographic_Wetness_Index_50m
## 5 geom_hr_L3_fl10_rplipshannon_UE_hr_5cells_hr
## 6 geom_hr_L3_fl10_rplipshape_UE_hr_10cells_hr
## 7 geom_hr_L50m_fl1_rplipshannon_UE_hr_20cells_hr
## 8 planc_DTM_50m_avg_ws7_50m
## 9 TRI_hr_ws48
## 10 Standardized_Height_50m
## k 4
## 1 Standardized_Height_50m
## 2 dtm_hr_CONVEX_r5
## 3 General_Curvature_hr
## 4 geom_hr_L3_fl1_rplipdominance_UE_hr_5cells_hr
## 5 geom_hr_L3_fl1_rplipshannon_UE_hr_5cells_hr
## 6 geom_hr_L3_fl1_rplippatchdensity_UE_hr_10cells_hr
## 7 longc_DTM_50m_avg_ws7_50m
## 8 geom_hr_L3_fl1_rpliprichness_UE_hr_60cells_hr
## 9 profc_ws23_hr_hr
## 10 geom_hr_L3_fl1_rplipmps_UE_hr_40cells_hr
## k 5
## 1 Standardized_Height_50m
## 2 ValleyDepth_10m
## 3 planc_ws23_hr_hr
## 4 geom_hr_L50m_fl10_rplipsimpson_UE_hr_5cells_hr
## 5 Texture_10m
## 6 geom_hr_L3_fl10_rpliprichness_UE_hr_5cells_hr
## 7 geom_hr_L50m_fl10_rplipshannon_UE_hr_5cells_hr
## 8 geom_hr_L50m_fl10_rplipmps_UE_hr_10cells_hr
## 9 crosc_ws3_hr_hr
## 10 geom_hr_L50m_fl1_rplipsimpson_UE_hr_60cells_hr
## [1] "10fold cv-error: 0.509259259259259"
## [1] "For predictors Standardized_Height_50m AND geom_hr_L3_fl10_rplipedgedensity_UE_hr_10cells_hr"
##
## preds 1 2 3 4 5
## 1 38 12 9 7 3
## 2 0 10 1 2 0
## 3 0 1 10 3 5
## 4 1 1 0 4 1
## 5 0 0 0 0 0
## [1] "Kappa overall = 0.391847227322806"
## [1] "Tau overall = 0.467592592592593"
## [1] "mean quality = 0.293716283044777"
## [1] "The quality is 0.293716283044777"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = NaN"
## [1] "###################### WITH PREDICTORS from the FW SELECTION ###################"
## [1] "10fold cv-error: 0.546296296296296"
## [1] "For predictors Standardized_Height_50m AND geom_hr_L3_fl10_rplipedgedensity_UE_hr_10cells_hr AND geom_hr_L50m_fl1_rplipshannon_UE_hr_5cells_hr AND geom_hr_L50m_fl1_rplipshannon_UE_hr_60cells_hr AND planc_DTM_50m_avg_ws3_50m AND geom_hr_L3_fl10_rplipmps_UE_hr_5cells_hr AND Normalized_Height_50m AND Mid_Slope_Positon_50m AND Slope_Height_50m AND LS_Factor_hr AND Profile_Curvature_50m AND ValleyDepth_10m AND Texture_10m AND geom_hr_L3_fl1_rplipmps_UE_hr_20cells_hr AND geom_hr_L3_fl10_rplippatchdensity_UE_hr_40cells_hr AND longc_ws11_10m AND Texture_50m AND terraintexture_hr_ws41_tp25 AND fischerk_ws33_hr AND Catchment_slope_50m AND Convexity_50m AND sagaTopographic_Wetness_Index_50m AND geom_hr_L3_fl10_rplipshannon_UE_hr_5cells_hr AND geom_hr_L3_fl10_rplipshape_UE_hr_10cells_hr AND geom_hr_L50m_fl1_rplipshannon_UE_hr_20cells_hr AND planc_DTM_50m_avg_ws7_50m AND TRI_hr_ws48 AND dtm_hr_CONVEX_r5 AND General_Curvature_hr AND geom_hr_L3_fl1_rplipdominance_UE_hr_5cells_hr AND geom_hr_L3_fl1_rplipshannon_UE_hr_5cells_hr AND geom_hr_L3_fl1_rplippatchdensity_UE_hr_10cells_hr AND longc_DTM_50m_avg_ws7_50m AND geom_hr_L3_fl1_rpliprichness_UE_hr_60cells_hr AND profc_ws23_hr_hr AND geom_hr_L3_fl1_rplipmps_UE_hr_40cells_hr AND planc_ws23_hr_hr AND geom_hr_L50m_fl10_rplipsimpson_UE_hr_5cells_hr AND geom_hr_L3_fl10_rpliprichness_UE_hr_5cells_hr AND geom_hr_L50m_fl10_rplipshannon_UE_hr_5cells_hr AND geom_hr_L50m_fl10_rplipmps_UE_hr_10cells_hr AND crosc_ws3_hr_hr AND geom_hr_L50m_fl1_rplipsimpson_UE_hr_60cells_hr"
##
## preds 1 2 3 4 5
## 1 38 4 4 0 1
## 2 1 20 2 1 2
## 3 0 0 14 0 3
## 4 0 0 0 15 0
## 5 0 0 0 0 3
## [1] "Kappa overall = 0.773953488372093"
## [1] "Tau overall = 0.791666666666667"
## [1] "mean quality = 0.667572463768116"
## [1] "The quality is 0.667572463768116"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = 0.774060526135238"
## [1] "######################WITH ALL PREDICTORS###################"
## [1] "10fold cv-error: 0.648148148148148"
##
## preds 1 2 3 4 5
## 1 39 21 20 16 9
## 2 0 3 0 0 0
## 3 0 0 0 0 0
## 4 0 0 0 0 0
## 5 0 0 0 0 0
## [1] "Kappa overall = 0.0492196878751501"
## [1] "Tau overall = 0.236111111111111"
## [1] "mean quality = 0.0992857142857143"
## [1] "The quality is 0.0992857142857143"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect

## [1] "######### Cramer's V = NaN"
Local terrain
i=1
for(i in 1:length(dependentlist)){
dep=dependentlist[i]
print(dependentlist_eng[i])
load(paste("../data/modeldata/SVMorigmodeldatawithgeoandgeom_",dep,".RData",sep=""))
preds <- evaluateforwardCV_anyerror(mypath=paste("../data/FSCV/SVM_localterrain/SVMwithgeoandgeom_fw_5fold_10p_",dep,"_localterrain",sep=""),kk=1:5,endround = 10,error = "cverror",geheim = "geheimerprederror",yrange=c(0,1))
predictors <- c(as.character(preds[1,1]),as.character(preds[2,1]))
print(preds)
predict_radial_full(modeldata=origmodeldata, dependent=dep, predictors=predictors,kappasum = F,tausum = F)
predictors = vector()
for (n in 1:ncol(preds)){
for (n2 in 1:nrow(preds)){
predictors <- c(predictors,as.character(preds[n2,n]))
}
}
print("###################### WITH PREDICTORS from the FW SELECTION ###################")
uniquepredictors <- unique(predictors)
predict_radial_full(modeldata=origmodeldata, dependent=dep, predictors=uniquepredictors)
#print("######################WITH ALL Local PREDICTORS###################")
#predict_radial_full(modeldata=origmodeldata, dependent=dep, predictors=unlist(paramsets[1]),printpreds = FALSE)
rm(origmodeldata,paramsets,paramsetnames,dependent)
}
## [1] "1a.2.1 - Potential as a habitat for drought-tolerant species"
## [1] "Prediction error at end is: 0.657575757575758"
## [2] "Prediction error at end is: 0.686580086580087"
## [3] "Prediction error at end is: 0.658441558441558"
## [4] "Prediction error at end is: 0.648917748917749"
## [5] "Prediction error at end is: 0.667099567099567"
## [6] "Prediction error at end is: 0.694805194805195"
## [7] "Prediction error at end is: 0.694372294372294"
## [8] "Prediction error at end is: 0.703896103896104"
## [9] "Prediction error at end is: 0.666233766233766"
## [10] "Prediction error at end is: 0.676190476190476"
## k 1 k 2 k 3
## 1 slope_DTM_50m_avg_ws9_50m slope_DTM_50m_avg_ws11_50m profc_ws5_hr_hr
## 2 planc_ws19_hr_hr profc_ws3_10m crosc_ws3_10m
## 3 Longitudinal_Curvature_hr planc_ws11_hr_hr minic_ws19_hr_hr
## 4 profc_DTM_50m_avg_ws11_50m crosc_ws7_hr_hr minic_ws3_10m
## 5 maxic_ws15_10m crosc_ws3_hr_hr planc_ws19_hr_hr
## 6 GeneralCurvature_10m slope_DTM_50m_avg_ws3_50m minic_ws29_hr_hr
## 7 maxic_DTM_50m_avg_ws9_50m ProfileCurvature_10m profc_ws7_hr_hr
## 8 profc_DTM_50m_avg_ws9_50m slope_ws5_10m minic_ws5_hr_hr
## 9 MaximalCurvature_10m longc_ws3_10m crosc_ws5_10m
## 10 slope_ws5_hr_hr slope_DTM_50m_avg_ws9_50m minic_ws13_hr_hr
## k 4 k 5
## 1 planc_ws11_hr_hr slope_DTM_50m_avg_ws11_50m
## 2 maxic_ws5_hr_hr profc_ws3_10m
## 3 slope_DTM_50m_avg_ws11_50m longc_ws7_10m
## 4 slope_ws3_hr_hr planc_ws19_hr_hr
## 5 TangentialCurvature_10m ProfileCurvature_10m
## 6 CrossSectionalCurvature_50m Flow_Line_Curvature_hr
## 7 planc_ws5_10m slope_ws19_hr_hr
## 8 slope_DTM_50m_avg_ws7_50m profc_ws13_hr_hr
## 9 longc_DTM_50m_avg_ws3_50m TangentialCurvature_10m
## 10 profc_ws7_hr_hr crosc_ws3_hr_hr
## [1] "10fold cv-error: 0.490740740740741"
## [1] "For predictors slope_DTM_50m_avg_ws9_50m AND planc_ws19_hr_hr"
##
## preds 1 2 3 4 5
## 1 0 0 0 0 0
## 2 0 0 0 0 0
## 3 1 0 4 0 1
## 4 3 11 12 28 6
## 5 0 2 5 10 25
## [1] "Kappa overall = 0.304018195602729"
## [1] "Tau overall = 0.409722222222222"
## [1] "mean quality = 0.216823425022183"
## [1] "The quality is 0.216823425022183"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = NaN"
## [1] "###################### WITH PREDICTORS from the FW SELECTION ###################"
## [1] "10fold cv-error: 0.583333333333333"
## [1] "For predictors slope_DTM_50m_avg_ws9_50m AND planc_ws19_hr_hr AND Longitudinal_Curvature_hr AND profc_DTM_50m_avg_ws11_50m AND maxic_ws15_10m AND GeneralCurvature_10m AND maxic_DTM_50m_avg_ws9_50m AND profc_DTM_50m_avg_ws9_50m AND MaximalCurvature_10m AND slope_ws5_hr_hr AND slope_DTM_50m_avg_ws11_50m AND profc_ws3_10m AND planc_ws11_hr_hr AND crosc_ws7_hr_hr AND crosc_ws3_hr_hr AND slope_DTM_50m_avg_ws3_50m AND ProfileCurvature_10m AND slope_ws5_10m AND longc_ws3_10m AND profc_ws5_hr_hr AND crosc_ws3_10m AND minic_ws19_hr_hr AND minic_ws3_10m AND minic_ws29_hr_hr AND profc_ws7_hr_hr AND minic_ws5_hr_hr AND crosc_ws5_10m AND minic_ws13_hr_hr AND maxic_ws5_hr_hr AND slope_ws3_hr_hr AND TangentialCurvature_10m AND CrossSectionalCurvature_50m AND planc_ws5_10m AND slope_DTM_50m_avg_ws7_50m AND longc_DTM_50m_avg_ws3_50m AND longc_ws7_10m AND Flow_Line_Curvature_hr AND slope_ws19_hr_hr AND profc_ws13_hr_hr"
##
## preds 1 2 3 4 5
## 1 2 0 0 0 0
## 2 0 7 0 0 0
## 3 1 2 9 0 0
## 4 1 4 9 33 5
## 5 0 0 3 5 27
## [1] "Kappa overall = 0.605695509309967"
## [1] "Tau overall = 0.652777777777778"
## [1] "mean quality = 0.533481781376518"
## [1] "The quality is 0.533481781376518"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect

## [1] "######### Cramer's V = 0.662776125620467"
## [1] "1a.2.2 - Potential as a habitat for moisture-tolerant species"
## [1] "Prediction error at end is: 0.667099567099567"
## [2] "Prediction error at end is: 0.648484848484848"
## [3] "Prediction error at end is: 0.638961038961039"
## [4] "Prediction error at end is: 0.61991341991342"
## [5] "Prediction error at end is: 0.619047619047619"
## [6] "Prediction error at end is: 0.573160173160173"
## [7] "Prediction error at end is: 0.583549783549783"
## [8] "Prediction error at end is: 0.545454545454545"
## [9] "Prediction error at end is: 0.535930735930736"
## [10] "Prediction error at end is: 0.564069264069264"
## k 1 k 2
## 1 crosc_ws5_10m slope_DTM_50m_avg_ws7_50m
## 2 CrossSectionalCurvature_hr maxic_ws11_hr_hr
## 3 minic_ws5_hr_hr maxic_ws13_hr_hr
## 4 minic_ws29_hr_hr maxic_ws9_hr_hr
## 5 longc_DTM_50m_avg_ws11_50m minic_ws29_hr_hr
## 6 planc_DTM_50m_avg_ws5_50m CrossSectionalCurvature_hr
## 7 slope_ws3_10m maxic_ws5_10m
## 8 dtm_hr_CONVEX_r30 maxic_ws23_hr_hr
## 9 minic_DTM_50m_avg_ws11_50m maxic_ws3_10m
## 10 Longitudinal_Curvature_hr planc_DTM_50m_avg_ws5_50m
## k 3 k 4
## 1 slope_DTM_50m_avg_ws7_50m minic_ws7_10m
## 2 Convexity_50m planc_ws29_hr_hr
## 3 planc_ws3_hr_hr CrossSectionalCurvature_hr
## 4 planc_ws7_10m maxic_ws7_10m
## 5 Convergence_Index_hr maxic_ws13_hr_hr
## 6 slope_DTM_50m_avg_ws11_50m LongitudinalCurvature_10m
## 7 Longitudinal_Curvature_hr maxic_ws5_10m
## 8 crosc_ws11_10m slope_ws5_hr_hr
## 9 Convergence_Index_50m crosc_ws5_hr_hr
## 10 slope_DTM_50m_avg_ws9_50m General_Curvature_50m
## k 5
## 1 Convexity_50m
## 2 slope_DTM_50m_avg_ws9_50m
## 3 crosc_ws11_10m
## 4 planc_ws5_10m
## 5 longc_ws5_hr_hr
## 6 slope_DTM_50m_avg_ws11_50m
## 7 maxic_ws11_10m
## 8 planc_ws7_10m
## 9 slope_ws11_hr_hr
## 10 Convergence_Index_hr
## [1] "10fold cv-error: 0.555555555555556"
## [1] "For predictors crosc_ws5_10m AND CrossSectionalCurvature_hr"
##
## preds 2 3 4 5
## 2 32 20 22 5
## 3 0 2 0 0
## 4 1 1 13 5
## 5 0 0 0 7
## [1] "Kappa overall = 0.2880859375"
## [1] "Tau overall = 0.333333333333333"
## [1] "mean quality = 0.302061259286323"
## [1] "The quality is 0.302061259286323"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = 0.456055648375919"
## [1] "###################### WITH PREDICTORS from the FW SELECTION ###################"
## [1] "10fold cv-error: 0.527777777777778"
## [1] "For predictors crosc_ws5_10m AND CrossSectionalCurvature_hr AND minic_ws5_hr_hr AND minic_ws29_hr_hr AND longc_DTM_50m_avg_ws11_50m AND planc_DTM_50m_avg_ws5_50m AND slope_ws3_10m AND dtm_hr_CONVEX_r30 AND minic_DTM_50m_avg_ws11_50m AND Longitudinal_Curvature_hr AND slope_DTM_50m_avg_ws7_50m AND maxic_ws11_hr_hr AND maxic_ws13_hr_hr AND maxic_ws9_hr_hr AND maxic_ws5_10m AND maxic_ws23_hr_hr AND maxic_ws3_10m AND Convexity_50m AND planc_ws3_hr_hr AND planc_ws7_10m AND Convergence_Index_hr AND slope_DTM_50m_avg_ws11_50m AND crosc_ws11_10m AND Convergence_Index_50m AND slope_DTM_50m_avg_ws9_50m AND minic_ws7_10m AND planc_ws29_hr_hr AND maxic_ws7_10m AND LongitudinalCurvature_10m AND slope_ws5_hr_hr AND crosc_ws5_hr_hr AND General_Curvature_50m AND planc_ws5_10m AND longc_ws5_hr_hr AND maxic_ws11_10m AND slope_ws11_hr_hr"
##
## preds 2 3 4 5
## 2 30 11 5 2
## 3 0 10 0 0
## 4 3 2 30 4
## 5 0 0 0 11
## [1] "Kappa overall = 0.648590021691974"
## [1] "Tau overall = 0.666666666666667"
## [1] "mean quality = 0.587973727040223"
## [1] "The quality is 0.587973727040223"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect

## [1] "######### Cramer's V = 0.701030983148723"
## [1] "1a.3 - Habitat for soil organisms"
## [1] "Prediction error at end is: 0.638961038961039"
## [2] "Prediction error at end is: 0.602164502164502"
## [3] "Prediction error at end is: 0.566666666666667"
## [4] "Prediction error at end is: 0.576190476190476"
## [5] "Prediction error at end is: 0.520779220779221"
## [6] "Prediction error at end is: 0.52034632034632"
## [7] "Prediction error at end is: 0.539393939393939"
## [8] "Prediction error at end is: 0.511688311688312"
## [9] "Prediction error at end is: 0.52987012987013"
## [10] "Prediction error at end is: 0.52987012987013"
## k 1 k 2
## 1 slope_DTM_50m_avg_ws9_50m slope_ws5_hr_hr
## 2 crosc_ws3_hr_hr PlanCurvature_10m
## 3 minic_ws5_10m longc_ws7_10m
## 4 PlanCurvature_10m planc_ws19_hr_hr
## 5 slope_DTM_50m_avg_ws11_50m slope_DTM_50m_avg_ws7_50m
## 6 profc_ws7_10m minic_ws5_hr_hr
## 7 maxic_DTM_50m_avg_ws5_50m Flow_Line_Curvature_hr
## 8 Total_Curvature_50m slope_DTM_50m_avg_ws5_50m
## 9 maxic_ws3_10m longc_DTM_50m_avg_ws7_50m
## 10 FlowLineCurvature_10m minic_DTM_50m_avg_ws11_50m
## k 3 k 4
## 1 crosc_ws11_hr_hr crosc_ws3_hr_hr
## 2 planc_ws5_10m Slope_50m
## 3 slope_DTM_50m_avg_ws7_50m maxic_DTM_50m_avg_ws11_50m
## 4 Longitudinal_Curvature_hr dtm_hr_CONVEX_r20
## 5 Convexity_50m slope_DTM_50m_avg_ws9_50m
## 6 minic_DTM_50m_avg_ws7_50m crosc_ws11_10m
## 7 longc_ws5_hr_hr crosc_DTM_50m_avg_ws11_50m
## 8 maxic_DTM_50m_avg_ws3_50m Convexity_50m
## 9 longc_DTM_50m_avg_ws5_50m minic_ws29_hr_hr
## 10 planc_ws7_10m Flow_Line_Curvature_hr
## k 5
## 1 slope_DTM_50m_avg_ws7_50m
## 2 LongitudinalCurvature_10m
## 3 PlanCurvature_10m
## 4 Flow_Line_Curvature_hr
## 5 minic_DTM_50m_avg_ws11_50m
## 6 Slope_50m
## 7 planc_ws3_hr_hr
## 8 longc_ws7_10m
## 9 Longitudinal_Curvature_hr
## 10 slope_DTM_50m_avg_ws9_50m
## [1] "10fold cv-error: 0.490740740740741"
## [1] "For predictors slope_DTM_50m_avg_ws9_50m AND crosc_ws3_hr_hr"
##
## preds 1 2 3 4
## 1 3 0 0 0
## 2 21 33 7 10
## 3 0 1 18 4
## 4 0 0 1 10
## [1] "Kappa overall = 0.428571428571428"
## [1] "Tau overall = 0.45679012345679"
## [1] "mean quality = 0.390994623655914"
## [1] "The quality is 0.390994623655914"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = 0.5399090352713"
## [1] "###################### WITH PREDICTORS from the FW SELECTION ###################"
## [1] "10fold cv-error: 0.509259259259259"
## [1] "For predictors slope_DTM_50m_avg_ws9_50m AND crosc_ws3_hr_hr AND minic_ws5_10m AND PlanCurvature_10m AND slope_DTM_50m_avg_ws11_50m AND profc_ws7_10m AND maxic_DTM_50m_avg_ws5_50m AND Total_Curvature_50m AND maxic_ws3_10m AND FlowLineCurvature_10m AND slope_ws5_hr_hr AND longc_ws7_10m AND planc_ws19_hr_hr AND slope_DTM_50m_avg_ws7_50m AND minic_ws5_hr_hr AND Flow_Line_Curvature_hr AND slope_DTM_50m_avg_ws5_50m AND longc_DTM_50m_avg_ws7_50m AND minic_DTM_50m_avg_ws11_50m AND crosc_ws11_hr_hr AND planc_ws5_10m AND Longitudinal_Curvature_hr AND Convexity_50m AND minic_DTM_50m_avg_ws7_50m AND longc_ws5_hr_hr AND maxic_DTM_50m_avg_ws3_50m AND longc_DTM_50m_avg_ws5_50m AND planc_ws7_10m AND Slope_50m AND maxic_DTM_50m_avg_ws11_50m AND dtm_hr_CONVEX_r20 AND crosc_ws11_10m AND crosc_DTM_50m_avg_ws11_50m AND minic_ws29_hr_hr AND LongitudinalCurvature_10m AND planc_ws3_hr_hr"
##
## preds 1 2 3 4
## 1 18 7 2 1
## 2 6 25 4 5
## 3 0 2 19 1
## 4 0 0 1 17
## [1] "Kappa overall = 0.636995827538248"
## [1] "Tau overall = 0.641975308641975"
## [1] "mean quality = 0.59369706503291"
## [1] "The quality is 0.59369706503291"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect

## [1] "######### Cramer's V = 0.680333202532746"
## [1] "1a.4 - Habitat for crops"
## [1] "Prediction error at end is: 0.176190476190476"
## [2] "Prediction error at end is: 0.222943722943723"
## [3] "Prediction error at end is: 0.213852813852814"
## [4] "Prediction error at end is: 0.223376623376623"
## [5] "Prediction error at end is: 0.204761904761905"
## [6] "Prediction error at end is: 0.213419913419913"
## [7] "Prediction error at end is: 0.222943722943723"
## [8] "Prediction error at end is: 0.232467532467532"
## [9] "Prediction error at end is: 0.232900432900433"
## [10] "Prediction error at end is: 0.241991341991342"
## k 1 k 2
## 1 slope_ws3_hr_hr slope_ws3_hr_hr
## 2 planc_ws29_hr_hr slope_ws11_10m
## 3 slope_ws15_10m slope_DTM_50m_avg_ws3_50m
## 4 planc_ws23_hr_hr Slope_50m
## 5 Plan_Curvature_hr Convexity_10m
## 6 Slope_hr longc_DTM_50m_avg_ws11_50m
## 7 planc_ws3_hr_hr crosc_ws5_10m
## 8 planc_DTM_50m_avg_ws11_50m crosc_ws23_hr_hr
## 9 Convergence_Index_50m Flow_Line_Curvature_50m
## 10 planc_DTM_50m_avg_ws7_50m Total_Curvature_hr
## k 3 k 4
## 1 slope_ws3_hr_hr slope_ws3_10m
## 2 minic_ws5_10m slope_ws5_10m
## 3 slope_ws15_10m crosc_ws5_10m
## 4 slope_DTM_50m_avg_ws3_50m Convexity_10m
## 5 slope_ws5_hr_hr slope_DTM_50m_avg_ws7_50m
## 6 minic_ws7_10m slope_DTM_50m_avg_ws11_50m
## 7 longc_ws7_hr_hr planc_ws3_hr_hr
## 8 minic_ws7_hr_hr slope_ws11_hr_hr
## 9 Slope_50m dtm_hr_CONVEX_r30
## 10 minic_ws15_10m slope_ws15_hr_hr
## k 5
## 1 slope_ws5_hr_hr
## 2 LongitudinalCurvature_10m
## 3 Convexity_10m
## 4 minic_ws11_10m
## 5 planc_ws9_hr_hr
## 6 planc_ws5_10m
## 7 slope_ws3_hr_hr
## 8 minic_ws7_10m
## 9 slope_DTM_50m_avg_ws9_50m
## 10 planc_ws11_10m
## [1] "10fold cv-error: 0.175925925925926"
## [1] "For predictors slope_ws3_hr_hr AND planc_ws29_hr_hr"
##
## preds 3 4 5
## 3 2 0 0
## 4 5 61 6
## 5 1 1 32
## [1] "Kappa overall = 0.761710794297352"
## [1] "Tau overall = 0.819444444444444"
## [1] "mean quality = 0.628538812785388"
## [1] "The quality is 0.628538812785388"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = 0.684411620853101"
## [1] "###################### WITH PREDICTORS from the FW SELECTION ###################"
## [1] "10fold cv-error: 0.185185185185185"
## [1] "For predictors slope_ws3_hr_hr AND planc_ws29_hr_hr AND slope_ws15_10m AND planc_ws23_hr_hr AND Plan_Curvature_hr AND Slope_hr AND planc_ws3_hr_hr AND planc_DTM_50m_avg_ws11_50m AND Convergence_Index_50m AND planc_DTM_50m_avg_ws7_50m AND slope_ws11_10m AND slope_DTM_50m_avg_ws3_50m AND Slope_50m AND Convexity_10m AND longc_DTM_50m_avg_ws11_50m AND crosc_ws5_10m AND crosc_ws23_hr_hr AND Flow_Line_Curvature_50m AND Total_Curvature_hr AND minic_ws5_10m AND slope_ws5_hr_hr AND minic_ws7_10m AND longc_ws7_hr_hr AND minic_ws7_hr_hr AND minic_ws15_10m AND slope_ws3_10m AND slope_ws5_10m AND slope_DTM_50m_avg_ws7_50m AND slope_DTM_50m_avg_ws11_50m AND slope_ws11_hr_hr AND dtm_hr_CONVEX_r30 AND slope_ws15_hr_hr AND LongitudinalCurvature_10m AND minic_ws11_10m AND planc_ws9_hr_hr AND planc_ws5_10m AND slope_DTM_50m_avg_ws9_50m AND planc_ws11_10m"
##
## preds 3 4 5
## 3 2 0 0
## 4 6 61 6
## 5 0 1 32
## [1] "Kappa overall = 0.760736196319018"
## [1] "Tau overall = 0.819444444444444"
## [1] "mean quality = 0.631612381612382"
## [1] "The quality is 0.631612381612382"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect

## [1] "######### Cramer's V = 0.694203111304538"
## [1] "1c.1 - Average precipitation retention capacity"
## [1] "Prediction error at end is: 0.611255411255411"
## [2] "Prediction error at end is: 0.583982683982684"
## [3] "Prediction error at end is: 0.583982683982684"
## [4] "Prediction error at end is: 0.556709956709957"
## [5] "Prediction error at end is: 0.592640692640693"
## [6] "Prediction error at end is: 0.62034632034632"
## [7] "Prediction error at end is: 0.611255411255411"
## [8] "Prediction error at end is: 0.611255411255411"
## [9] "Prediction error at end is: 0.611255411255411"
## [10] "Prediction error at end is: 0.611255411255411"
## k 1 k 2
## 1 slope_DTM_50m_avg_ws5_50m ProfileCurvature_10m
## 2 Flow_Line_Curvature_50m slope_DTM_50m_avg_ws11_50m
## 3 maxic_DTM_50m_avg_ws11_50m crosc_DTM_50m_avg_ws11_50m
## 4 dtm_hr_CONVEX_r10 crosc_DTM_50m_avg_ws9_50m
## 5 crosc_ws3_10m planc_ws5_hr_hr
## 6 slope_ws11_10m dtm_hr_CONVEX_r30
## 7 slope_DTM_50m_avg_ws7_50m planc_ws9_hr_hr
## 8 Plan_Curvature_hr minic_ws11_hr_hr
## 9 planc_ws13_hr_hr profc_ws15_10m
## 10 slope_ws15_10m minic_DTM_50m_avg_ws7_50m
## k 3 k 4
## 1 crosc_DTM_50m_avg_ws11_50m crosc_ws19_hr_hr
## 2 minic_ws19_hr_hr GeneralCurvature_10m
## 3 minic_DTM_50m_avg_ws9_50m longc_ws11_10m
## 4 minic_ws3_hr_hr Plan_Curvature_hr
## 5 minic_DTM_50m_avg_ws11_50m profc_ws3_10m
## 6 Plan_Curvature_hr minic_ws15_10m
## 7 crosc_DTM_50m_avg_ws9_50m slope_ws7_10m
## 8 profc_DTM_50m_avg_ws9_50m minic_DTM_50m_avg_ws5_50m
## 9 profc_ws5_hr_hr slope_ws29_hr_hr
## 10 CrossSectionalCurvature_50m Total_Curvature_50m
## k 5
## 1 slope_DTM_50m_avg_ws7_50m
## 2 slope_ws7_10m
## 3 minic_ws19_hr_hr
## 4 planc_ws15_hr_hr
## 5 Total_Curvature_hr
## 6 planc_DTM_50m_avg_ws5_50m
## 7 planc_ws11_hr_hr
## 8 longc_ws11_10m
## 9 maxic_DTM_50m_avg_ws3_50m
## 10 slope_DTM_50m_avg_ws9_50m
## [1] "10fold cv-error: 0.518518518518519"
## [1] "For predictors slope_DTM_50m_avg_ws5_50m AND Flow_Line_Curvature_50m"
##
## preds 1 2 3 4 5
## 1 11 1 3 3 5
## 2 15 44 9 14 2
## 3 0 0 0 0 0
## 4 0 0 0 1 0
## 5 0 0 0 0 0
## [1] "Kappa overall = 0.227297743533297"
## [1] "Tau overall = 0.398148148148148"
## [1] "mean quality = 0.172535259717922"
## [1] "The quality is 0.172535259717922"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = NaN"
## [1] "###################### WITH PREDICTORS from the FW SELECTION ###################"
## [1] "10fold cv-error: 0.527777777777778"
## [1] "For predictors slope_DTM_50m_avg_ws5_50m AND Flow_Line_Curvature_50m AND maxic_DTM_50m_avg_ws11_50m AND dtm_hr_CONVEX_r10 AND crosc_ws3_10m AND slope_ws11_10m AND slope_DTM_50m_avg_ws7_50m AND Plan_Curvature_hr AND planc_ws13_hr_hr AND slope_ws15_10m AND ProfileCurvature_10m AND slope_DTM_50m_avg_ws11_50m AND crosc_DTM_50m_avg_ws11_50m AND crosc_DTM_50m_avg_ws9_50m AND planc_ws5_hr_hr AND dtm_hr_CONVEX_r30 AND planc_ws9_hr_hr AND minic_ws11_hr_hr AND profc_ws15_10m AND minic_DTM_50m_avg_ws7_50m AND minic_ws19_hr_hr AND minic_DTM_50m_avg_ws9_50m AND minic_ws3_hr_hr AND minic_DTM_50m_avg_ws11_50m AND profc_DTM_50m_avg_ws9_50m AND profc_ws5_hr_hr AND CrossSectionalCurvature_50m AND crosc_ws19_hr_hr AND GeneralCurvature_10m AND longc_ws11_10m AND profc_ws3_10m AND minic_ws15_10m AND slope_ws7_10m AND minic_DTM_50m_avg_ws5_50m AND slope_ws29_hr_hr AND Total_Curvature_50m AND planc_ws15_hr_hr AND Total_Curvature_hr AND planc_DTM_50m_avg_ws5_50m AND planc_ws11_hr_hr AND maxic_DTM_50m_avg_ws3_50m AND slope_DTM_50m_avg_ws9_50m"
##
## preds 1 2 3 4 5
## 1 16 0 3 1 3
## 2 10 45 8 12 2
## 3 0 0 1 0 0
## 4 0 0 0 5 0
## 5 0 0 0 0 2
## [1] "Kappa overall = 0.437274549098196"
## [1] "Tau overall = 0.548611111111111"
## [1] "mean quality = 0.343217893217893"
## [1] "The quality is 0.343217893217893"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect

## [1] "######### Cramer's V = 0.495174407613578"
## [1] "1c.1 - Minimum precipitation retention capacity"
## [1] "Prediction error at end is: 0.75974025974026"
## [2] "Prediction error at end is: 0.767532467532468"
## [3] "Prediction error at end is: 0.767099567099567"
## [4] "Prediction error at end is: 0.738961038961039"
## [5] "Prediction error at end is: 0.73030303030303"
## [6] "Prediction error at end is: 0.738961038961039"
## [7] "Prediction error at end is: 0.738528138528138"
## [8] "Prediction error at end is: 0.766666666666667"
## [9] "Prediction error at end is: 0.767099567099567"
## [10] "Prediction error at end is: 0.767099567099567"
## k 1 k 2
## 1 crosc_ws11_10m minic_ws11_10m
## 2 minic_ws15_hr_hr profc_ws15_10m
## 3 planc_ws5_10m Longitudinal_Curvature_hr
## 4 minic_DTM_50m_avg_ws11_50m PlanCurvature_10m
## 5 Total_Curvature_50m Maximal_Curvature_50m
## 6 Plan_Curvature_50m Profile_Curvature_50m
## 7 crosc_DTM_50m_avg_ws3_50m Convergence_Index_hr
## 8 planc_ws3_hr_hr minic_DTM_50m_avg_ws5_50m
## 9 planc_ws11_10m profc_DTM_50m_avg_ws11_50m
## 10 Maximal_Curvature_50m planc_ws3_hr_hr
## k 3 k 4
## 1 planc_ws7_10m minic_DTM_50m_avg_ws5_50m
## 2 CrossSectionalCurvature_50m maxic_ws3_10m
## 3 minic_DTM_50m_avg_ws3_50m longc_ws29_hr_hr
## 4 crosc_ws15_hr_hr Flow_Line_Curvature_50m
## 5 dtm_hr_CONVEX_r30 minic_ws13_hr_hr
## 6 slope_DTM_50m_avg_ws9_50m slope_ws11_10m
## 7 planc_ws3_10m minic_DTM_50m_avg_ws7_50m
## 8 maxic_ws29_hr_hr planc_ws3_hr_hr
## 9 maxic_ws5_10m LongitudinalCurvature_10m
## 10 maxic_ws7_hr_hr MinimalCurvature_10m
## k 5
## 1 longc_DTM_50m_avg_ws3_50m
## 2 planc_ws5_10m
## 3 Profile_Curvature_hr
## 4 minic_ws11_10m
## 5 Convexity_10m
## 6 dtm_hr_CONVEX_r30
## 7 minic_DTM_50m_avg_ws3_50m
## 8 profc_ws11_10m
## 9 minic_ws5_hr_hr
## 10 planc_ws29_hr_hr
## [1] "10fold cv-error: 0.666666666666667"
## [1] "For predictors crosc_ws11_10m AND minic_ws15_hr_hr"
##
## preds 1 2 3 4 5
## 1 0 0 0 0 0
## 2 6 21 16 15 6
## 3 0 0 1 0 0
## 4 4 4 4 10 2
## 5 2 1 1 1 14
## [1] "Kappa overall = 0.250671441360788"
## [1] "Tau overall = 0.282407407407407"
## [1] "mean quality = 0.223664178012004"
## [1] "The quality is 0.223664178012004"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = NaN"
## [1] "###################### WITH PREDICTORS from the FW SELECTION ###################"
## [1] "10fold cv-error: 0.666666666666667"
## [1] "For predictors crosc_ws11_10m AND minic_ws15_hr_hr AND planc_ws5_10m AND minic_DTM_50m_avg_ws11_50m AND Total_Curvature_50m AND Plan_Curvature_50m AND crosc_DTM_50m_avg_ws3_50m AND planc_ws3_hr_hr AND planc_ws11_10m AND Maximal_Curvature_50m AND minic_ws11_10m AND profc_ws15_10m AND Longitudinal_Curvature_hr AND PlanCurvature_10m AND Profile_Curvature_50m AND Convergence_Index_hr AND minic_DTM_50m_avg_ws5_50m AND profc_DTM_50m_avg_ws11_50m AND planc_ws7_10m AND CrossSectionalCurvature_50m AND minic_DTM_50m_avg_ws3_50m AND crosc_ws15_hr_hr AND dtm_hr_CONVEX_r30 AND slope_DTM_50m_avg_ws9_50m AND planc_ws3_10m AND maxic_ws29_hr_hr AND maxic_ws5_10m AND maxic_ws7_hr_hr AND maxic_ws3_10m AND longc_ws29_hr_hr AND Flow_Line_Curvature_50m AND minic_ws13_hr_hr AND slope_ws11_10m AND minic_DTM_50m_avg_ws7_50m AND LongitudinalCurvature_10m AND MinimalCurvature_10m AND longc_DTM_50m_avg_ws3_50m AND Profile_Curvature_hr AND Convexity_10m AND profc_ws11_10m AND minic_ws5_hr_hr AND planc_ws29_hr_hr"
##
## preds 1 2 3 4 5
## 1 3 0 0 0 0
## 2 4 25 8 7 3
## 3 1 1 12 2 1
## 4 1 0 1 16 3
## 5 3 0 1 1 15
## [1] "Kappa overall = 0.558257793499889"
## [1] "Tau overall = 0.571759259259259"
## [1] "mean quality = 0.45739247311828"
## [1] "The quality is 0.45739247311828"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect

## [1] "######### Cramer's V = 0.581372327644911"
## [1] "1c.2 - Retention capacity for heavy precipitation events"
## [1] "Prediction error at end is: 0.333333333333333"
## [2] "Prediction error at end is: 0.296536796536797"
## [3] "Prediction error at end is: 0.287445887445887"
## [4] "Prediction error at end is: 0.287445887445887"
## [5] "Prediction error at end is: 0.287445887445887"
## [6] "Prediction error at end is: 0.278354978354978"
## [7] "Prediction error at end is: 0.278354978354978"
## [8] "Prediction error at end is: 0.287445887445887"
## [9] "Prediction error at end is: 0.287445887445887"
## [10] "Prediction error at end is: 0.278354978354978"
## k 1 k 2
## 1 crosc_ws7_10m longc_ws15_hr_hr
## 2 maxic_ws11_10m Minimal_Curvature_50m
## 3 Total_Curvature_50m Minimal_Curvature_hr
## 4 slope_DTM_50m_avg_ws3_50m minic_ws15_hr_hr
## 5 crosc_DTM_50m_avg_ws5_50m profc_ws15_hr_hr
## 6 crosc_ws3_hr_hr maxic_ws11_10m
## 7 slope_ws11_10m longc_ws13_hr_hr
## 8 Profile_Curvature_50m longc_ws11_hr_hr
## 9 longc_DTM_50m_avg_ws3_50m minic_ws19_hr_hr
## 10 profc_ws19_hr_hr planc_ws11_10m
## k 3 k 4
## 1 crosc_ws11_10m longc_ws5_10m
## 2 Maximal_Curvature_50m minic_ws3_hr_hr
## 3 Minimal_Curvature_50m maxic_ws7_10m
## 4 Convexity_50m longc_ws15_hr_hr
## 5 Flow_Line_Curvature_50m maxic_ws15_10m
## 6 Total_Curvature_hr maxic_DTM_50m_avg_ws5_50m
## 7 Plan_Curvature_hr profc_ws15_hr_hr
## 8 slope_DTM_50m_avg_ws5_50m Longitudinal_Curvature_hr
## 9 maxic_ws11_10m minic_ws29_hr_hr
## 10 profc_ws11_10m Minimal_Curvature_hr
## k 5
## 1 Minimal_Curvature_50m
## 2 minic_ws15_10m
## 3 minic_ws5_10m
## 4 longc_ws15_10m
## 5 maxic_ws23_hr_hr
## 6 minic_ws11_10m
## 7 minic_ws3_hr_hr
## 8 General_Curvature_hr
## 9 maxic_ws3_hr_hr
## 10 General_Curvature_50m
## [1] "10fold cv-error: 0.259259259259259"
## [1] "For predictors crosc_ws7_10m AND maxic_ws11_10m"
##
## preds 1 2 3 4 5
## 1 75 10 6 3 8
## 2 0 1 0 0 0
## 3 0 0 0 0 0
## 4 0 0 0 5 0
## 5 0 0 0 0 0
## [1] "Kappa overall = 0.264193792581378"
## [1] "Tau overall = 0.6875"
## [1] "mean quality = 0.29024064171123"
## [1] "The quality is 0.29024064171123"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = NaN"
## [1] "###################### WITH PREDICTORS from the FW SELECTION ###################"
## [1] "10fold cv-error: 0.277777777777778"
## [1] "For predictors crosc_ws7_10m AND maxic_ws11_10m AND Total_Curvature_50m AND slope_DTM_50m_avg_ws3_50m AND crosc_DTM_50m_avg_ws5_50m AND crosc_ws3_hr_hr AND slope_ws11_10m AND Profile_Curvature_50m AND longc_DTM_50m_avg_ws3_50m AND profc_ws19_hr_hr AND longc_ws15_hr_hr AND Minimal_Curvature_50m AND Minimal_Curvature_hr AND minic_ws15_hr_hr AND profc_ws15_hr_hr AND longc_ws13_hr_hr AND longc_ws11_hr_hr AND minic_ws19_hr_hr AND planc_ws11_10m AND crosc_ws11_10m AND Maximal_Curvature_50m AND Convexity_50m AND Flow_Line_Curvature_50m AND Total_Curvature_hr AND Plan_Curvature_hr AND slope_DTM_50m_avg_ws5_50m AND profc_ws11_10m AND longc_ws5_10m AND minic_ws3_hr_hr AND maxic_ws7_10m AND maxic_ws15_10m AND maxic_DTM_50m_avg_ws5_50m AND Longitudinal_Curvature_hr AND minic_ws29_hr_hr AND minic_ws15_10m AND minic_ws5_10m AND longc_ws15_10m AND maxic_ws23_hr_hr AND minic_ws11_10m AND General_Curvature_hr AND maxic_ws3_hr_hr AND General_Curvature_50m"
##
## preds 1 2 3 4 5
## 1 75 6 6 0 6
## 2 0 5 0 0 0
## 3 0 0 0 0 0
## 4 0 0 0 8 0
## 5 0 0 0 0 2
## [1] "Kappa overall = 0.573122529644269"
## [1] "Tau overall = 0.791666666666667"
## [1] "mean quality = 0.502199413489736"
## [1] "The quality is 0.502199413489736"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect

## [1] "######### Cramer's V = NaN"
## [1] "1c.3 - groundwater reformation rate"
## [1] "Prediction error at end is: 0.658441558441558"
## [2] "Prediction error at end is: 0.649350649350649"
## [3] "Prediction error at end is: 0.658874458874459"
## [4] "Prediction error at end is: 0.630735930735931"
## [5] "Prediction error at end is: 0.639393939393939"
## [6] "Prediction error at end is: 0.658441558441558"
## [7] "Prediction error at end is: 0.658441558441558"
## [8] "Prediction error at end is: 0.658441558441558"
## [9] "Prediction error at end is: 0.658441558441558"
## [10] "Prediction error at end is: 0.649350649350649"
## k 1 k 2
## 1 minic_ws15_10m slope_DTM_50m_avg_ws7_50m
## 2 maxic_ws7_hr_hr slope_ws3_10m
## 3 minic_ws29_hr_hr Convexity_50m
## 4 minic_ws3_hr_hr FlowLineCurvature_10m
## 5 profc_ws3_hr_hr slope_DTM_50m_avg_ws5_50m
## 6 minic_ws7_10m crosc_ws7_10m
## 7 LongitudinalCurvature_10m dtm_hr_CONVEX_r10
## 8 planc_DTM_50m_avg_ws11_50m General_Curvature_hr
## 9 crosc_ws5_10m slope_ws7_10m
## 10 maxic_ws3_10m crosc_ws23_hr_hr
## k 3 k 4
## 1 crosc_ws23_hr_hr crosc_ws3_hr_hr
## 2 CrossSectionalCurvature_hr slope_DTM_50m_avg_ws9_50m
## 3 crosc_ws19_hr_hr maxic_ws3_10m
## 4 Convexity_50m slope_ws7_10m
## 5 planc_ws29_hr_hr CrossSectionalCurvature_hr
## 6 planc_DTM_50m_avg_ws3_50m Tangential_Curvature_hr
## 7 Flow_Line_Curvature_hr Convexity_50m
## 8 maxic_ws3_hr_hr slope_ws15_10m
## 9 crosc_ws7_10m Minimal_Curvature_hr
## 10 crosc_ws5_10m minic_ws11_10m
## k 5
## 1 slope_DTM_50m_avg_ws9_50m
## 2 minic_DTM_50m_avg_ws3_50m
## 3 profc_ws7_hr_hr
## 4 longc_DTM_50m_avg_ws9_50m
## 5 Profile_Curvature_hr
## 6 General_Curvature_hr
## 7 minic_ws15_10m
## 8 minic_ws13_hr_hr
## 9 CrossSectionalCurvature_hr
## 10 maxic_ws3_hr_hr
## [1] "10fold cv-error: 0.555555555555556"
## [1] "For predictors minic_ws15_10m AND maxic_ws7_hr_hr"
##
## preds 1 2 3 4 5
## 1 1 0 0 0 0
## 2 13 37 10 14 9
## 3 0 0 1 0 0
## 4 0 0 1 4 0
## 5 0 2 2 1 13
## [1] "Kappa overall = 0.289833080424886"
## [1] "Tau overall = 0.398148148148148"
## [1] "mean quality = 0.251926548397137"
## [1] "The quality is 0.251926548397137"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = 0.38726358510718"
## [1] "###################### WITH PREDICTORS from the FW SELECTION ###################"
## [1] "10fold cv-error: 0.685185185185185"
## [1] "For predictors minic_ws15_10m AND maxic_ws7_hr_hr AND minic_ws29_hr_hr AND minic_ws3_hr_hr AND profc_ws3_hr_hr AND minic_ws7_10m AND LongitudinalCurvature_10m AND planc_DTM_50m_avg_ws11_50m AND crosc_ws5_10m AND maxic_ws3_10m AND slope_DTM_50m_avg_ws7_50m AND slope_ws3_10m AND Convexity_50m AND FlowLineCurvature_10m AND slope_DTM_50m_avg_ws5_50m AND crosc_ws7_10m AND dtm_hr_CONVEX_r10 AND General_Curvature_hr AND slope_ws7_10m AND crosc_ws23_hr_hr AND CrossSectionalCurvature_hr AND crosc_ws19_hr_hr AND planc_ws29_hr_hr AND planc_DTM_50m_avg_ws3_50m AND Flow_Line_Curvature_hr AND maxic_ws3_hr_hr AND crosc_ws3_hr_hr AND slope_DTM_50m_avg_ws9_50m AND Tangential_Curvature_hr AND slope_ws15_10m AND Minimal_Curvature_hr AND minic_ws11_10m AND minic_DTM_50m_avg_ws3_50m AND profc_ws7_hr_hr AND longc_DTM_50m_avg_ws9_50m AND Profile_Curvature_hr AND minic_ws13_hr_hr"
##
## preds 1 2 3 4 5
## 1 3 0 0 0 0
## 2 11 38 10 5 9
## 3 0 0 2 0 0
## 4 0 0 1 12 0
## 5 0 1 1 2 13
## [1] "Kappa overall = 0.468373123307901"
## [1] "Tau overall = 0.537037037037037"
## [1] "mean quality = 0.394131274131274"
## [1] "The quality is 0.394131274131274"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect

## [1] "######### Cramer's V = 0.549432082090476"
## [1] "1c.4 - Potential for providing nutrients for plants"
## [1] "Prediction error at end is: 0.352380952380952"
## [2] "Prediction error at end is: 0.388311688311688"
## [3] "Prediction error at end is: 0.36969696969697"
## [4] "Prediction error at end is: 0.341991341991342"
## [5] "Prediction error at end is: 0.351948051948052"
## [6] "Prediction error at end is: 0.370995670995671"
## [7] "Prediction error at end is: 0.352380952380952"
## [8] "Prediction error at end is: 0.343290043290043"
## [9] "Prediction error at end is: 0.343290043290043"
## [10] "Prediction error at end is: 0.343290043290043"
## k 1 k 2
## 1 minic_ws15_hr_hr minic_ws9_hr_hr
## 2 crosc_ws3_hr_hr Profile_Curvature_50m
## 3 minic_ws5_hr_hr profc_ws23_hr_hr
## 4 maxic_ws3_10m minic_ws5_hr_hr
## 5 planc_DTM_50m_avg_ws7_50m ProfileCurvature_10m
## 6 planc_DTM_50m_avg_ws11_50m Convexity_10m
## 7 Slope_50m crosc_ws3_hr_hr
## 8 minic_ws7_hr_hr Total_Curvature_hr
## 9 Convergence_Index_50m profc_ws15_hr_hr
## 10 Convergence_Index_hr minic_ws7_hr_hr
## k 3 k 4
## 1 minic_ws9_hr_hr minic_ws7_hr_hr
## 2 Tangential_Curvature_50m crosc_DTM_50m_avg_ws5_50m
## 3 dtm_hr_CONVEX_r30 General_Curvature_50m
## 4 minic_ws7_hr_hr longc_ws15_10m
## 5 slope_ws3_hr_hr Convergence_Index_hr
## 6 profc_ws23_hr_hr minic_DTM_50m_avg_ws11_50m
## 7 slope_ws15_hr_hr Convexity_10m
## 8 crosc_ws3_10m planc_ws11_10m
## 9 Profile_Curvature_50m Total_Curvature_50m
## 10 Plan_Curvature_50m Minimal_Curvature_50m
## k 5
## 1 LongitudinalCurvature_10m
## 2 minic_ws7_10m
## 3 crosc_ws3_hr_hr
## 4 General_Curvature_hr
## 5 planc_ws3_hr_hr
## 6 slope_ws5_hr_hr
## 7 profc_ws29_hr_hr
## 8 dtm_hr_CONVEX_r30
## 9 minic_ws15_10m
## 10 Flow_Line_Curvature_hr
## [1] "10fold cv-error: 0.324074074074074"
## [1] "For predictors minic_ws15_hr_hr AND crosc_ws3_hr_hr"
##
## preds 1 3 5
## 1 64 9 15
## 3 0 0 0
## 5 1 2 17
## [1] "Kappa overall = 0.450226244343891"
## [1] "Tau overall = 0.625"
## [1] "mean quality = 0.401605136436597"
## [1] "The quality is 0.401605136436597"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = NaN"
## [1] "###################### WITH PREDICTORS from the FW SELECTION ###################"
## [1] "10fold cv-error: 0.324074074074074"
## [1] "For predictors minic_ws15_hr_hr AND crosc_ws3_hr_hr AND minic_ws5_hr_hr AND maxic_ws3_10m AND planc_DTM_50m_avg_ws7_50m AND planc_DTM_50m_avg_ws11_50m AND Slope_50m AND minic_ws7_hr_hr AND Convergence_Index_50m AND Convergence_Index_hr AND minic_ws9_hr_hr AND Profile_Curvature_50m AND profc_ws23_hr_hr AND ProfileCurvature_10m AND Convexity_10m AND Total_Curvature_hr AND profc_ws15_hr_hr AND Tangential_Curvature_50m AND dtm_hr_CONVEX_r30 AND slope_ws3_hr_hr AND slope_ws15_hr_hr AND crosc_ws3_10m AND Plan_Curvature_50m AND crosc_DTM_50m_avg_ws5_50m AND General_Curvature_50m AND longc_ws15_10m AND minic_DTM_50m_avg_ws11_50m AND planc_ws11_10m AND Total_Curvature_50m AND Minimal_Curvature_50m AND LongitudinalCurvature_10m AND minic_ws7_10m AND General_Curvature_hr AND planc_ws3_hr_hr AND slope_ws5_hr_hr AND profc_ws29_hr_hr AND minic_ws15_10m AND Flow_Line_Curvature_hr"
##
## preds 1 3 5
## 1 64 7 6
## 3 0 2 0
## 5 1 2 26
## [1] "Kappa overall = 0.697320021019443"
## [1] "Tau overall = 0.777777777777778"
## [1] "mean quality = 0.581729381729382"
## [1] "The quality is 0.581729381729382"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect

## [1] "######### Cramer's V = 0.638035811797989"
## [1] "1c.5 - Potential as a CO2 sink"
## [1] "Prediction error at end is: 0.502164502164502"
## [2] "Prediction error at end is: 0.446320346320346"
## [3] "Prediction error at end is: 0.38008658008658"
## [4] "Prediction error at end is: 0.351948051948052"
## [5] "Prediction error at end is: 0.37012987012987"
## [6] "Prediction error at end is: 0.37965367965368"
## [7] "Prediction error at end is: 0.370995670995671"
## [8] "Prediction error at end is: 0.370995670995671"
## [9] "Prediction error at end is: 0.361904761904762"
## [10] "Prediction error at end is: 0.370995670995671"
## k 1 k 2
## 1 minic_ws11_hr_hr crosc_ws13_hr_hr
## 2 maxic_ws3_10m minic_ws11_hr_hr
## 3 MaximalCurvature_10m minic_ws13_hr_hr
## 4 maxic_ws3_hr_hr minic_ws5_hr_hr
## 5 maxic_ws19_hr_hr maxic_ws3_10m
## 6 Convexity_10m ProfileCurvature_10m
## 7 dtm_hr_CONVEX_r30 crosc_DTM_50m_avg_ws5_50m
## 8 slope_ws3_10m planc_ws3_hr_hr
## 9 Minimal_Curvature_50m crosc_ws5_hr_hr
## 10 planc_DTM_50m_avg_ws7_50m maxic_ws5_10m
## k 3 k 4
## 1 minic_ws11_hr_hr slope_ws15_hr_hr
## 2 minic_DTM_50m_avg_ws5_50m planc_ws5_hr_hr
## 3 profc_ws3_10m longc_ws3_hr_hr
## 4 longc_ws3_hr_hr slope_DTM_50m_avg_ws7_50m
## 5 minic_ws15_10m crosc_ws15_hr_hr
## 6 minic_ws13_hr_hr profc_ws5_hr_hr
## 7 minic_ws9_hr_hr planc_DTM_50m_avg_ws11_50m
## 8 longc_ws15_10m MaximalCurvature_10m
## 9 Maximal_Curvature_hr longc_ws3_10m
## 10 Profile_Curvature_50m Slope_hr
## k 5
## 1 TangentialCurvature_10m
## 2 crosc_ws13_hr_hr
## 3 minic_ws3_hr_hr
## 4 minic_ws7_hr_hr
## 5 dtm_hr_CONVEX_r30
## 6 slope_DTM_50m_avg_ws11_50m
## 7 MaximalCurvature_10m
## 8 maxic_ws3_hr_hr
## 9 planc_DTM_50m_avg_ws9_50m
## 10 longc_DTM_50m_avg_ws9_50m
## [1] "10fold cv-error: 0.324074074074074"
## [1] "For predictors minic_ws11_hr_hr AND maxic_ws3_10m"
##
## preds 1 2 3 4 5
## 1 44 0 3 2 1
## 2 0 0 0 0 0
## 3 0 0 0 0 0
## 4 7 1 15 31 4
## 5 0 0 0 0 0
## [1] "Kappa overall = 0.505"
## [1] "Tau overall = 0.618055555555555"
## [1] "mean quality = 0.257719298245614"
## [1] "The quality is 0.257719298245614"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = NaN"
## [1] "###################### WITH PREDICTORS from the FW SELECTION ###################"
## [1] "10fold cv-error: 0.314814814814815"
## [1] "For predictors minic_ws11_hr_hr AND maxic_ws3_10m AND MaximalCurvature_10m AND maxic_ws3_hr_hr AND maxic_ws19_hr_hr AND Convexity_10m AND dtm_hr_CONVEX_r30 AND slope_ws3_10m AND Minimal_Curvature_50m AND planc_DTM_50m_avg_ws7_50m AND crosc_ws13_hr_hr AND minic_ws13_hr_hr AND minic_ws5_hr_hr AND ProfileCurvature_10m AND crosc_DTM_50m_avg_ws5_50m AND planc_ws3_hr_hr AND crosc_ws5_hr_hr AND maxic_ws5_10m AND minic_DTM_50m_avg_ws5_50m AND profc_ws3_10m AND longc_ws3_hr_hr AND minic_ws15_10m AND minic_ws9_hr_hr AND longc_ws15_10m AND Maximal_Curvature_hr AND Profile_Curvature_50m AND slope_ws15_hr_hr AND planc_ws5_hr_hr AND slope_DTM_50m_avg_ws7_50m AND crosc_ws15_hr_hr AND profc_ws5_hr_hr AND planc_DTM_50m_avg_ws11_50m AND longc_ws3_10m AND Slope_hr AND TangentialCurvature_10m AND minic_ws3_hr_hr AND minic_ws7_hr_hr AND slope_DTM_50m_avg_ws11_50m AND planc_DTM_50m_avg_ws9_50m AND longc_DTM_50m_avg_ws9_50m"
##
## preds 1 2 3 4 5
## 1 46 0 1 1 1
## 2 0 0 0 0 0
## 3 0 0 6 0 0
## 4 5 1 11 32 4
## 5 0 0 0 0 0
## [1] "Kappa overall = 0.645320197044335"
## [1] "Tau overall = 0.722222222222222"
## [1] "mean quality = 0.355555555555556"
## [1] "The quality is 0.355555555555556"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect

## [1] "######### Cramer's V = NaN"
## [1] "1d.1 - Potential for retention of heavy metals"
## [1] "Prediction error at end is: 0.425974025974026"
## [2] "Prediction error at end is: 0.425541125541126"
## [3] "Prediction error at end is: 0.388744588744589"
## [4] "Prediction error at end is: 0.369264069264069"
## [5] "Prediction error at end is: 0.379220779220779"
## [6] "Prediction error at end is: 0.37012987012987"
## [7] "Prediction error at end is: 0.351515151515152"
## [8] "Prediction error at end is: 0.37012987012987"
## [9] "Prediction error at end is: 0.37965367965368"
## [10] "Prediction error at end is: 0.37012987012987"
## k 1 k 2
## 1 crosc_ws13_hr_hr slope_ws11_10m
## 2 slope_ws19_hr_hr dtm_hr_CONVEX_r30
## 3 minic_ws11_10m longc_DTM_50m_avg_ws9_50m
## 4 maxic_ws3_10m TotalCurvature_10m
## 5 planc_ws3_hr_hr Total_Curvature_50m
## 6 minic_DTM_50m_avg_ws3_50m minic_ws11_10m
## 7 MaximalCurvature_10m minic_ws23_hr_hr
## 8 slope_ws7_10m longc_DTM_50m_avg_ws5_50m
## 9 slope_DTM_50m_avg_ws3_50m maxic_ws3_10m
## 10 maxic_ws11_hr_hr maxic_ws5_hr_hr
## k 3 k 4
## 1 minic_ws9_hr_hr slope_ws5_10m
## 2 maxic_ws3_10m minic_ws11_10m
## 3 minic_ws11_10m maxic_ws23_hr_hr
## 4 minic_ws5_hr_hr minic_ws29_hr_hr
## 5 MaximalCurvature_10m dtm_hr_CONVEX_r30
## 6 crosc_DTM_50m_avg_ws5_50m longc_ws9_hr_hr
## 7 crosc_ws3_hr_hr Convexity_10m
## 8 maxic_ws3_hr_hr General_Curvature_50m
## 9 slope_DTM_50m_avg_ws5_50m planc_DTM_50m_avg_ws11_50m
## 10 maxic_ws15_hr_hr slope_ws11_10m
## k 5
## 1 Slope_10m
## 2 longc_ws19_hr_hr
## 3 Minimal_Curvature_50m
## 4 dtm_hr_CONVEX_r30
## 5 longc_DTM_50m_avg_ws9_50m
## 6 profc_DTM_50m_avg_ws9_50m
## 7 maxic_ws7_10m
## 8 profc_DTM_50m_avg_ws5_50m
## 9 slope_DTM_50m_avg_ws11_50m
## 10 minic_DTM_50m_avg_ws3_50m
## [1] "10fold cv-error: 0.37962962962963"
## [1] "For predictors crosc_ws13_hr_hr AND slope_ws19_hr_hr"
##
## preds 1 2 3 4 5
## 1 38 5 8 3 11
## 2 0 0 0 0 0
## 3 0 0 0 0 0
## 4 0 0 0 0 0
## 5 4 2 2 4 31
## [1] "Kappa overall = 0.409090909090909"
## [1] "Tau overall = 0.548611111111111"
## [1] "mean quality = 0.224959742351047"
## [1] "The quality is 0.224959742351047"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = NaN"
## [1] "###################### WITH PREDICTORS from the FW SELECTION ###################"
## [1] "10fold cv-error: 0.351851851851852"
## [1] "For predictors crosc_ws13_hr_hr AND slope_ws19_hr_hr AND minic_ws11_10m AND maxic_ws3_10m AND planc_ws3_hr_hr AND minic_DTM_50m_avg_ws3_50m AND MaximalCurvature_10m AND slope_ws7_10m AND slope_DTM_50m_avg_ws3_50m AND maxic_ws11_hr_hr AND slope_ws11_10m AND dtm_hr_CONVEX_r30 AND longc_DTM_50m_avg_ws9_50m AND TotalCurvature_10m AND Total_Curvature_50m AND minic_ws23_hr_hr AND longc_DTM_50m_avg_ws5_50m AND maxic_ws5_hr_hr AND minic_ws9_hr_hr AND minic_ws5_hr_hr AND crosc_DTM_50m_avg_ws5_50m AND crosc_ws3_hr_hr AND maxic_ws3_hr_hr AND slope_DTM_50m_avg_ws5_50m AND maxic_ws15_hr_hr AND slope_ws5_10m AND maxic_ws23_hr_hr AND minic_ws29_hr_hr AND longc_ws9_hr_hr AND Convexity_10m AND General_Curvature_50m AND planc_DTM_50m_avg_ws11_50m AND Slope_10m AND longc_ws19_hr_hr AND Minimal_Curvature_50m AND profc_DTM_50m_avg_ws9_50m AND maxic_ws7_10m AND profc_DTM_50m_avg_ws5_50m AND slope_DTM_50m_avg_ws11_50m"
##
## preds 1 2 3 4 5
## 1 41 4 7 3 5
## 2 0 1 0 0 0
## 3 0 0 2 0 0
## 4 0 0 0 2 0
## 5 1 2 1 2 37
## [1] "Kappa overall = 0.629984925311772"
## [1] "Tau overall = 0.710648148148148"
## [1] "mean quality = 0.414307181889149"
## [1] "The quality is 0.414307181889149"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect

## [1] "######### Cramer's V = 0.55548001516698"
## [1] "1d.2 - Potential for transforming organic contaminants"
## [1] "Prediction error at end is: 0.683549783549784"
## [2] "Prediction error at end is: 0.674891774891775"
## [3] "Prediction error at end is: 0.627272727272727"
## [4] "Prediction error at end is: 0.645887445887446"
## [5] "Prediction error at end is: 0.646320346320346"
## [6] "Prediction error at end is: 0.638528138528139"
## [7] "Prediction error at end is: 0.638961038961039"
## [8] "Prediction error at end is: 0.61991341991342"
## [9] "Prediction error at end is: 0.628138528138528"
## [10] "Prediction error at end is: 0.656277056277056"
## k 1 k 2
## 1 slope_ws7_10m MaximalCurvature_10m
## 2 crosc_ws15_10m profc_DTM_50m_avg_ws7_50m
## 3 planc_ws5_hr_hr planc_DTM_50m_avg_ws9_50m
## 4 Total_Curvature_50m Plan_Curvature_hr
## 5 minic_ws11_10m profc_DTM_50m_avg_ws5_50m
## 6 longc_ws3_hr_hr maxic_DTM_50m_avg_ws7_50m
## 7 TangentialCurvature_10m Convexity_10m
## 8 Slope_hr longc_DTM_50m_avg_ws7_50m
## 9 Plan_Curvature_hr longc_ws3_hr_hr
## 10 Convexity_10m maxic_ws13_hr_hr
## k 3 k 4
## 1 Minimal_Curvature_50m minic_ws5_hr_hr
## 2 minic_ws11_hr_hr crosc_ws15_10m
## 3 profc_ws11_hr_hr slope_DTM_50m_avg_ws5_50m
## 4 longc_DTM_50m_avg_ws9_50m crosc_ws7_10m
## 5 profc_DTM_50m_avg_ws9_50m Slope_10m
## 6 dtm_hr_CONVEX_r30 minic_ws19_hr_hr
## 7 slope_ws29_hr_hr slope_DTM_50m_avg_ws7_50m
## 8 dtm_hr_CONVEX_r20 Convexity_50m
## 9 maxic_DTM_50m_avg_ws5_50m dtm_hr_CONVEX_r10
## 10 Tangential_Curvature_50m minic_DTM_50m_avg_ws3_50m
## k 5
## 1 crosc_ws11_10m
## 2 slope_DTM_50m_avg_ws9_50m
## 3 minic_ws3_hr_hr
## 4 longc_ws3_hr_hr
## 5 longc_ws15_hr_hr
## 6 profc_ws3_10m
## 7 Minimal_Curvature_hr
## 8 planc_DTM_50m_avg_ws9_50m
## 9 CrossSectionalCurvature_hr
## 10 planc_ws15_hr_hr
## [1] "10fold cv-error: 0.509259259259259"
## [1] "For predictors slope_ws7_10m AND crosc_ws15_10m"
##
## preds 1 2 3 4 5
## 1 0 0 0 0 0
## 2 0 0 0 0 0
## 3 10 18 22 2 9
## 4 0 0 0 3 1
## 5 0 4 6 4 29
## [1] "Kappa overall = 0.292490598083222"
## [1] "Tau overall = 0.375"
## [1] "mean quality = 0.235105604055196"
## [1] "The quality is 0.235105604055196"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = NaN"
## [1] "###################### WITH PREDICTORS from the FW SELECTION ###################"
## [1] "10fold cv-error: 0.546296296296296"
## [1] "For predictors slope_ws7_10m AND crosc_ws15_10m AND planc_ws5_hr_hr AND Total_Curvature_50m AND minic_ws11_10m AND longc_ws3_hr_hr AND TangentialCurvature_10m AND Slope_hr AND Plan_Curvature_hr AND Convexity_10m AND MaximalCurvature_10m AND profc_DTM_50m_avg_ws7_50m AND planc_DTM_50m_avg_ws9_50m AND profc_DTM_50m_avg_ws5_50m AND maxic_DTM_50m_avg_ws7_50m AND longc_DTM_50m_avg_ws7_50m AND maxic_ws13_hr_hr AND Minimal_Curvature_50m AND minic_ws11_hr_hr AND profc_ws11_hr_hr AND longc_DTM_50m_avg_ws9_50m AND profc_DTM_50m_avg_ws9_50m AND dtm_hr_CONVEX_r30 AND slope_ws29_hr_hr AND dtm_hr_CONVEX_r20 AND maxic_DTM_50m_avg_ws5_50m AND Tangential_Curvature_50m AND minic_ws5_hr_hr AND slope_DTM_50m_avg_ws5_50m AND crosc_ws7_10m AND Slope_10m AND minic_ws19_hr_hr AND slope_DTM_50m_avg_ws7_50m AND Convexity_50m AND dtm_hr_CONVEX_r10 AND minic_DTM_50m_avg_ws3_50m AND crosc_ws11_10m AND slope_DTM_50m_avg_ws9_50m AND minic_ws3_hr_hr AND longc_ws15_hr_hr AND profc_ws3_10m AND Minimal_Curvature_hr AND CrossSectionalCurvature_hr AND planc_ws15_hr_hr"
##
## preds 1 2 3 4 5
## 1 1 0 0 0 0
## 2 0 6 0 0 0
## 3 9 14 27 2 5
## 4 0 0 0 4 0
## 5 0 2 1 3 34
## [1] "Kappa overall = 0.533253301320528"
## [1] "Tau overall = 0.583333333333333"
## [1] "mean quality = 0.407648902821317"
## [1] "The quality is 0.407648902821317"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect

## [1] "######### Cramer's V = 0.583706053095214"
## [1] "1d.3 - Potential as filter and buffer for organic contaminants"
## [1] "Prediction error at end is: 0.0372294372294372"
## [2] "Prediction error at end is: 0.0372294372294372"
## [3] "Prediction error at end is: 0.0372294372294372"
## [4] "Prediction error at end is: 0.0372294372294372"
## [5] "Prediction error at end is: 0.0372294372294372"
## [6] "Prediction error at end is: 0.0372294372294372"
## [7] "Prediction error at end is: 0.0372294372294372"
## [8] "Prediction error at end is: 0.0372294372294372"
## [9] "Prediction error at end is: 0.0372294372294372"
## [10] "Prediction error at end is: 0.0372294372294372"
## k 1 k 2 k 3
## 1 PlanCurvature_10m PlanCurvature_10m crosc_ws11_10m
## 2 planc_ws11_hr_hr planc_ws11_hr_hr crosc_ws15_10m
## 3 planc_ws13_hr_hr planc_ws9_hr_hr crosc_ws3_10m
## 4 planc_ws19_hr_hr crosc_DTM_50m_avg_ws11_50m crosc_ws5_10m
## 5 Convexity_10m maxic_DTM_50m_avg_ws11_50m crosc_ws7_10m
## 6 planc_ws9_hr_hr longc_ws7_10m longc_ws11_10m
## 7 crosc_DTM_50m_avg_ws11_50m profc_ws5_10m longc_ws15_10m
## 8 maxic_DTM_50m_avg_ws11_50m profc_ws7_10m longc_ws3_10m
## 9 minic_DTM_50m_avg_ws11_50m LongitudinalCurvature_10m longc_ws5_10m
## 10 profc_DTM_50m_avg_ws9_50m maxic_DTM_50m_avg_ws3_50m longc_ws7_10m
## k 4 k 5
## 1 crosc_ws11_10m PlanCurvature_10m
## 2 crosc_ws15_10m planc_ws11_hr_hr
## 3 crosc_ws3_10m planc_ws19_hr_hr
## 4 crosc_ws5_10m Convexity_10m
## 5 crosc_ws7_10m minic_ws15_10m
## 6 longc_ws11_10m minic_ws11_10m
## 7 longc_ws15_10m minic_ws7_10m
## 8 longc_ws3_10m slope_ws15_10m
## 9 longc_ws5_10m Tangential_Curvature_50m
## 10 longc_ws7_10m crosc_DTM_50m_avg_ws11_50m
## [1] "10fold cv-error: 0.0185185185185185"
## [1] "For predictors PlanCurvature_10m AND planc_ws11_hr_hr"
##
## preds 4 5
## 4 2 0
## 5 2 104
## [1] "Kappa overall = 0.658227848101266"
## [1] "Tau overall = 0.962962962962963"
## [1] "mean quality = 0.740566037735849"
## [1] "The quality is 0.740566037735849"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = 0.518568491248852"
## [1] "###################### WITH PREDICTORS from the FW SELECTION ###################"
## [1] "10fold cv-error: 0.0370370370370371"
## [1] "For predictors PlanCurvature_10m AND planc_ws11_hr_hr AND planc_ws13_hr_hr AND planc_ws19_hr_hr AND Convexity_10m AND planc_ws9_hr_hr AND crosc_DTM_50m_avg_ws11_50m AND maxic_DTM_50m_avg_ws11_50m AND minic_DTM_50m_avg_ws11_50m AND profc_DTM_50m_avg_ws9_50m AND longc_ws7_10m AND profc_ws5_10m AND profc_ws7_10m AND LongitudinalCurvature_10m AND maxic_DTM_50m_avg_ws3_50m AND crosc_ws11_10m AND crosc_ws15_10m AND crosc_ws3_10m AND crosc_ws5_10m AND crosc_ws7_10m AND longc_ws11_10m AND longc_ws15_10m AND longc_ws3_10m AND longc_ws5_10m AND minic_ws15_10m AND minic_ws11_10m AND minic_ws7_10m AND slope_ws15_10m AND Tangential_Curvature_50m"
##
## preds 4 5
## 4 0 0
## 5 4 104
## [1] "Kappa overall = 0"
## [1] "Tau overall = 0.925925925925926"
## [1] "mean quality = 0.481481481481482"
## [1] "The quality is 0.481481481481482"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect

## [1] "######### Cramer's V = NaN"
## [1] "1d.4 - Potential for retention of water-soluble contaminants"
## [1] "Prediction error at end is: 0.593073593073593"
## [2] "Prediction error at end is: 0.556709956709957"
## [3] "Prediction error at end is: 0.538095238095238"
## [4] "Prediction error at end is: 0.547186147186147"
## [5] "Prediction error at end is: 0.538095238095238"
## [6] "Prediction error at end is: 0.51991341991342"
## [7] "Prediction error at end is: 0.510822510822511"
## [8] "Prediction error at end is: 0.51991341991342"
## [9] "Prediction error at end is: 0.501298701298701"
## [10] "Prediction error at end is: 0.510822510822511"
## k 1 k 2
## 1 minic_ws11_10m maxic_ws29_hr_hr
## 2 slope_ws5_hr_hr slope_ws3_hr_hr
## 3 Flow_Line_Curvature_50m Flow_Line_Curvature_50m
## 4 Slope_10m crosc_ws5_10m
## 5 Maximal_Curvature_hr slope_DTM_50m_avg_ws5_50m
## 6 LongitudinalCurvature_10m Flow_Line_Curvature_hr
## 7 minic_DTM_50m_avg_ws3_50m minic_DTM_50m_avg_ws3_50m
## 8 General_Curvature_hr minic_ws7_10m
## 9 Total_Curvature_50m MaximalCurvature_10m
## 10 slope_ws5_10m General_Curvature_50m
## k 3 k 4
## 1 crosc_ws5_hr_hr slope_ws7_10m
## 2 crosc_ws15_hr_hr crosc_ws19_hr_hr
## 3 slope_ws15_10m minic_ws5_hr_hr
## 4 profc_ws5_10m minic_DTM_50m_avg_ws5_50m
## 5 planc_ws5_hr_hr maxic_DTM_50m_avg_ws11_50m
## 6 minic_DTM_50m_avg_ws5_50m slope_ws15_10m
## 7 Total_Curvature_hr slope_DTM_50m_avg_ws3_50m
## 8 maxic_ws11_10m planc_DTM_50m_avg_ws11_50m
## 9 slope_DTM_50m_avg_ws5_50m planc_ws9_hr_hr
## 10 maxic_DTM_50m_avg_ws11_50m longc_ws15_10m
## k 5
## 1 crosc_ws5_10m
## 2 Slope_hr
## 3 ProfileCurvature_10m
## 4 minic_ws5_hr_hr
## 5 slope_ws11_hr_hr
## 6 slope_ws15_10m
## 7 maxic_ws5_10m
## 8 minic_ws7_10m
## 9 longc_ws3_hr_hr
## 10 maxic_DTM_50m_avg_ws11_50m
## [1] "10fold cv-error: 0.472222222222222"
## [1] "For predictors minic_ws11_10m AND slope_ws5_hr_hr"
##
## preds 1 2 3 4 5
## 1 43 8 7 9 3
## 2 0 0 0 0 0
## 3 0 0 4 0 0
## 4 4 6 6 13 2
## 5 0 0 0 0 3
## [1] "Kappa overall = 0.360526315789474"
## [1] "Tau overall = 0.479166666666667"
## [1] "mean quality = 0.303275039745628"
## [1] "The quality is 0.303275039745628"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = NaN"
## [1] "###################### WITH PREDICTORS from the FW SELECTION ###################"
## [1] "10fold cv-error: 0.481481481481481"
## [1] "For predictors minic_ws11_10m AND slope_ws5_hr_hr AND Flow_Line_Curvature_50m AND Slope_10m AND Maximal_Curvature_hr AND LongitudinalCurvature_10m AND minic_DTM_50m_avg_ws3_50m AND General_Curvature_hr AND Total_Curvature_50m AND slope_ws5_10m AND maxic_ws29_hr_hr AND slope_ws3_hr_hr AND crosc_ws5_10m AND slope_DTM_50m_avg_ws5_50m AND Flow_Line_Curvature_hr AND minic_ws7_10m AND MaximalCurvature_10m AND General_Curvature_50m AND crosc_ws5_hr_hr AND crosc_ws15_hr_hr AND slope_ws15_10m AND profc_ws5_10m AND planc_ws5_hr_hr AND minic_DTM_50m_avg_ws5_50m AND Total_Curvature_hr AND maxic_ws11_10m AND maxic_DTM_50m_avg_ws11_50m AND slope_ws7_10m AND crosc_ws19_hr_hr AND minic_ws5_hr_hr AND slope_DTM_50m_avg_ws3_50m AND planc_DTM_50m_avg_ws11_50m AND planc_ws9_hr_hr AND longc_ws15_10m AND Slope_hr AND ProfileCurvature_10m AND slope_ws11_hr_hr AND maxic_ws5_10m AND longc_ws3_hr_hr"
##
## preds 1 2 3 4 5
## 1 46 9 6 7 1
## 2 0 2 0 0 0
## 3 0 0 8 0 0
## 4 1 3 3 15 2
## 5 0 0 0 0 5
## [1] "Kappa overall = 0.550526726492392"
## [1] "Tau overall = 0.62962962962963"
## [1] "mean quality = 0.475891840607211"
## [1] "The quality is 0.475891840607211"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect

## [1] "######### Cramer's V = 0.619729938181675"
## [1] "1d.5 - Potential as buffer for acidic contaminants"
## [1] "Prediction error at end is: 0.63030303030303"
## [2] "Prediction error at end is: 0.665800865800866"
## [3] "Prediction error at end is: 0.657142857142857"
## [4] "Prediction error at end is: 0.703463203463203"
## [5] "Prediction error at end is: 0.694372294372294"
## [6] "Prediction error at end is: 0.685714285714286"
## [7] "Prediction error at end is: 0.666233766233766"
## [8] "Prediction error at end is: 0.666666666666667"
## [9] "Prediction error at end is: 0.675757575757576"
## [10] "Prediction error at end is: 0.674891774891775"
## k 1 k 2
## 1 planc_ws11_10m Profile_Curvature_50m
## 2 slope_DTM_50m_avg_ws11_50m planc_ws29_hr_hr
## 3 minic_DTM_50m_avg_ws5_50m minic_ws23_hr_hr
## 4 maxic_DTM_50m_avg_ws11_50m planc_ws7_10m
## 5 slope_ws7_10m Convexity_50m
## 6 planc_ws7_10m maxic_DTM_50m_avg_ws7_50m
## 7 profc_ws19_hr_hr dtm_hr_CONVEX_r10
## 8 minic_ws7_hr_hr planc_ws23_hr_hr
## 9 Convexity_10m minic_ws5_10m
## 10 crosc_DTM_50m_avg_ws5_50m planc_ws3_hr_hr
## k 3 k 4
## 1 crosc_DTM_50m_avg_ws9_50m General_Curvature_50m
## 2 slope_ws7_10m Slope_hr
## 3 planc_ws5_10m profc_DTM_50m_avg_ws11_50m
## 4 slope_ws29_hr_hr profc_DTM_50m_avg_ws3_50m
## 5 crosc_DTM_50m_avg_ws5_50m Profile_Curvature_50m
## 6 profc_DTM_50m_avg_ws11_50m Minimal_Curvature_hr
## 7 crosc_ws11_10m planc_ws7_10m
## 8 minic_ws3_hr_hr maxic_DTM_50m_avg_ws11_50m
## 9 slope_DTM_50m_avg_ws3_50m profc_ws29_hr_hr
## 10 planc_ws3_10m minic_ws15_hr_hr
## k 5
## 1 Profile_Curvature_50m
## 2 profc_ws5_10m
## 3 maxic_DTM_50m_avg_ws5_50m
## 4 profc_DTM_50m_avg_ws3_50m
## 5 crosc_DTM_50m_avg_ws7_50m
## 6 longc_ws23_hr_hr
## 7 minic_DTM_50m_avg_ws3_50m
## 8 longc_ws15_10m
## 9 Plan_Curvature_hr
## 10 Convergence_Index_50m
## [1] "10fold cv-error: 0.583333333333333"
## [1] "For predictors planc_ws11_10m AND slope_DTM_50m_avg_ws11_50m"
##
## preds 1 2 3 4 5
## 1 39 11 16 12 7
## 2 0 13 2 1 0
## 3 0 0 2 0 1
## 4 0 0 0 3 1
## 5 0 0 0 0 0
## [1] "Kappa overall = 0.297538579262849"
## [1] "Tau overall = 0.409722222222222"
## [1] "mean quality = 0.242402738873327"
## [1] "The quality is 0.242402738873327"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = NaN"
## [1] "###################### WITH PREDICTORS from the FW SELECTION ###################"
## [1] "10fold cv-error: 0.555555555555556"
## [1] "For predictors planc_ws11_10m AND slope_DTM_50m_avg_ws11_50m AND minic_DTM_50m_avg_ws5_50m AND maxic_DTM_50m_avg_ws11_50m AND slope_ws7_10m AND planc_ws7_10m AND profc_ws19_hr_hr AND minic_ws7_hr_hr AND Convexity_10m AND crosc_DTM_50m_avg_ws5_50m AND Profile_Curvature_50m AND planc_ws29_hr_hr AND minic_ws23_hr_hr AND Convexity_50m AND maxic_DTM_50m_avg_ws7_50m AND dtm_hr_CONVEX_r10 AND planc_ws23_hr_hr AND minic_ws5_10m AND planc_ws3_hr_hr AND crosc_DTM_50m_avg_ws9_50m AND planc_ws5_10m AND slope_ws29_hr_hr AND profc_DTM_50m_avg_ws11_50m AND crosc_ws11_10m AND minic_ws3_hr_hr AND slope_DTM_50m_avg_ws3_50m AND planc_ws3_10m AND General_Curvature_50m AND Slope_hr AND profc_DTM_50m_avg_ws3_50m AND Minimal_Curvature_hr AND profc_ws29_hr_hr AND minic_ws15_hr_hr AND profc_ws5_10m AND maxic_DTM_50m_avg_ws5_50m AND crosc_DTM_50m_avg_ws7_50m AND longc_ws23_hr_hr AND minic_DTM_50m_avg_ws3_50m AND longc_ws15_10m AND Plan_Curvature_hr AND Convergence_Index_50m"
##
## preds 1 2 3 4 5
## 1 38 7 11 3 3
## 2 1 17 0 1 0
## 3 0 0 9 0 2
## 4 0 0 0 12 0
## 5 0 0 0 0 4
## [1] "Kappa overall = 0.637497003116759"
## [1] "Tau overall = 0.675925925925926"
## [1] "mean quality = 0.572111222111222"
## [1] "The quality is 0.572111222111222"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect

## [1] "######### Cramer's V = 0.706105756645892"
Geomorphons
i=1
for(i in 1:length(dependentlist)){
dep=dependentlist[i]
print(dependentlist_eng[i])
load(paste("../data/modeldata/SVMorigmodeldatawithgeoandgeom_",dep,".RData",sep=""))
preds <- evaluateforwardCV_anyerror(mypath=paste("../data/FSCV/SVM_geoms/SVMwithgeoandgeom_fw_5fold_10p_",dep,"_NA",sep=""),kk=1:5,endround = 10,error = "cverror",geheim = "geheimerprederror",yrange=c(0,1))
predictors <- c(as.character(preds[1,1]),as.character(preds[2,1]))
print(preds)
predict_radial_full(modeldata=origmodeldata, dependent=dep, predictors=predictors,kappasum = F,tausum = F)
predictors = vector()
for (n in 1:ncol(preds)){
for (n2 in 1:nrow(preds)){
predictors <- c(predictors,as.character(preds[n2,n]))
}
}
print("###################### WITH PREDICTORS from the FW SELECTION ###################")
uniquepredictors <- unique(predictors)
predict_radial_full(modeldata=origmodeldata, dependent=dep, predictors=uniquepredictors)
#print("######################WITH ALL GEOMORPHONS###################")
predict_radial_full(modeldata=origmodeldata, dependent=dep, predictors=unlist(paramsets[6]),printpreds = FALSE)
rm(origmodeldata,paramsets,paramsetnames,dependent)
}
## [1] "1a.2.1 - Potential as a habitat for drought-tolerant species"
## [1] "Prediction error at end is: 0.620779220779221"
## [2] "Prediction error at end is: 0.62987012987013"
## [3] "Prediction error at end is: 0.666233766233766"
## [4] "Prediction error at end is: 0.675324675324675"
## [5] "Prediction error at end is: 0.666233766233766"
## [6] "Prediction error at end is: 0.666233766233766"
## [7] "Prediction error at end is: 0.647619047619048"
## [8] "Prediction error at end is: 0.648051948051948"
## [9] "Prediction error at end is: 0.657142857142857"
## [10] "Prediction error at end is: 0.675324675324675"
## k 1 k 2 k 3
## 1 geom_dtm_10m_hyd_fl5_L10 geom_10m_fl1_L50 geom_10m_fl3_L3
## 2 geom_dtm_10m_hyd_fl5_L8 geom_10m_fl1_L110 geom_10m_fl4_L9
## 3 geom_dtm_10m_hyd_fl5_L5 geom_10m_fl10_L21 geom_dtm_10m_hyd_fl5_L13
## 4 geom_dtm_10m_hyd_fl5_L80 geom_10m_fl10_L140 geom_dtm_10m_hyd_fl5_L14
## 5 geom_dtm_10m_hyd_fl5_L7 geom_10m_fl2_L20 geom_dtm_10m_hyd_fl5_L15
## 6 geom_dtm_10m_hyd_fl5_L9 geom_10m_fl2_L5 geom_dtm_10m_hyd_fl5_L7
## 7 geom_dtm_10m_hyd_fl5_L12 geom_10m_fl2_L8 geom_dtm_10m_hyd_fl5_L8
## 8 geom_dtm_10m_hyd_fl5_L110 geom_10m_fl4_L10 geom_10m_fl10_L100
## 9 geom_dtm_10m_hyd_fl5_L13 geom_10m_fl1_L47 geom_10m_fl10_L110
## 10 geom_10m_fl10_L140 geom_10m_fl2_L50 geom_10m_fl10_L120
## k 4 k 5
## 1 geom_10m_fl4_L10 geom_10m_fl4_L9
## 2 geom_10m_fl4_L23 geom_10m_fl8_L10
## 3 geom_10m_fl4_L28 geom_10m_fl10_L140
## 4 geom_10m_fl4_L9 geom_dtm_10m_hyd_fl5_L7
## 5 geom_10m_fl4_L14 geom_dtm_10m_hyd_fl5_L34
## 6 geom_10m_fl4_L37 geom_10m_fl3_L3
## 7 geom_dtm_10m_hyd_fl5_L10 geom_dtm_10m_hyd_fl5_L40
## 8 geom_dtm_10m_hyd_fl5_L80 geom_dtm_10m_hyd_fl5_L41
## 9 geom_10m_fl4_L38 geom_dtm_10m_hyd_fl5_L42
## 10 geom_10m_fl4_L120 geom_10m_fl3_L7
## [1] "10fold cv-error: 0.546296296296296"
## [1] "For predictors geom_dtm_10m_hyd_fl5_L10 AND geom_dtm_10m_hyd_fl5_L8"
##
## preds 1 2 3 4 5
## 1 0 0 0 0 0
## 2 0 0 0 0 0
## 3 0 0 0 0 0
## 4 4 13 19 34 16
## 5 0 0 2 4 16
## [1] "Kappa overall = 0.185647425897036"
## [1] "Tau overall = 0.328703703703704"
## [1] "mean quality = 0.159766081871345"
## [1] "The quality is 0.159766081871345"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = NaN"
## [1] "###################### WITH PREDICTORS from the FW SELECTION ###################"
## [1] "10fold cv-error: 0.62037037037037"
## [1] "For predictors geom_dtm_10m_hyd_fl5_L10 AND geom_dtm_10m_hyd_fl5_L8 AND geom_dtm_10m_hyd_fl5_L5 AND geom_dtm_10m_hyd_fl5_L80 AND geom_dtm_10m_hyd_fl5_L7 AND geom_dtm_10m_hyd_fl5_L9 AND geom_dtm_10m_hyd_fl5_L12 AND geom_dtm_10m_hyd_fl5_L110 AND geom_dtm_10m_hyd_fl5_L13 AND geom_10m_fl10_L140 AND geom_10m_fl1_L50 AND geom_10m_fl1_L110 AND geom_10m_fl10_L21 AND geom_10m_fl2_L20 AND geom_10m_fl2_L5 AND geom_10m_fl2_L8 AND geom_10m_fl4_L10 AND geom_10m_fl1_L47 AND geom_10m_fl2_L50 AND geom_10m_fl3_L3 AND geom_10m_fl4_L9 AND geom_dtm_10m_hyd_fl5_L14 AND geom_dtm_10m_hyd_fl5_L15 AND geom_10m_fl10_L100 AND geom_10m_fl10_L110 AND geom_10m_fl10_L120 AND geom_10m_fl4_L23 AND geom_10m_fl4_L28 AND geom_10m_fl4_L14 AND geom_10m_fl4_L37 AND geom_10m_fl4_L38 AND geom_10m_fl4_L120 AND geom_10m_fl8_L10 AND geom_dtm_10m_hyd_fl5_L34 AND geom_dtm_10m_hyd_fl5_L40 AND geom_dtm_10m_hyd_fl5_L41 AND geom_dtm_10m_hyd_fl5_L42 AND geom_10m_fl3_L7"
##
## preds 1 2 3 4 5
## 1 0 0 0 0 0
## 2 0 0 0 0 0
## 3 0 0 0 0 0
## 4 4 13 20 38 18
## 5 0 0 1 0 14
## [1] "Kappa overall = 0.209411764705882"
## [1] "Tau overall = 0.351851851851852"
## [1] "mean quality = 0.166568914956012"
## [1] "The quality is 0.166568914956012"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = NaN"
## [1] "10fold cv-error: 0.648148148148148"
##
## preds 1 2 3 4 5
## 1 0 0 0 0 0
## 2 0 0 0 0 0
## 3 0 0 0 0 0
## 4 4 13 21 38 32
## 5 0 0 0 0 0
## [1] "Kappa overall = 0"
## [1] "Tau overall = 0.189814814814815"
## [1] "mean quality = 0.0703703703703704"
## [1] "The quality is 0.0703703703703704"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect

## [1] "######### Cramer's V = NaN"
## [1] "1a.2.2 - Potential as a habitat for moisture-tolerant species"
## [1] "Prediction error at end is: 0.583982683982684"
## [2] "Prediction error at end is: 0.638961038961039"
## [3] "Prediction error at end is: 0.638961038961039"
## [4] "Prediction error at end is: 0.657142857142857"
## [5] "Prediction error at end is: 0.647619047619048"
## [6] "Prediction error at end is: 0.647619047619048"
## [7] "Prediction error at end is: 0.647186147186147"
## [8] "Prediction error at end is: 0.675324675324675"
## [9] "Prediction error at end is: 0.684415584415584"
## [10] "Prediction error at end is: 0.674891774891775"
## k 1 k 2
## 1 geom_10m_fl8_L16 geom_10m_fl8_L8
## 2 geom_dtm_10m_hyd_fl5_L21 geom_10m_fl8_L80
## 3 geom_10m_fl10_L110 geom_10m_fl10_L80
## 4 geom_10m_fl4_L8 geom_10m_fl8_L90
## 5 geom_10m_fl2_L3 geom_10m_fl10_L120
## 6 geom_10m_fl4_L19 geom_10m_fl10_L26
## 7 geom_10m_fl1_L43 geom_10m_fl10_L110
## 8 geom_10m_fl1_L44 geom_dtm_10m_hyd_fl5_L11
## 9 geom_10m_fl1_L100 geom_10m_fl10_L40
## 10 geom_10m_fl1_L80 geom_10m_fl10_L70
## k 3 k 4
## 1 geom_10m_fl8_L12 geom_10m_fl10_L150
## 2 geom_10m_fl4_L3 geom_dtm_10m_hyd_fl5_L25
## 3 geom_dtm_10m_hyd_fl5_L27 geom_10m_fl10_L80
## 4 geom_10m_fl4_L10 geom_dtm_10m_hyd_fl5_L10
## 5 geom_dtm_10m_hyd_fl5_L30 geom_10m_fl10_L90
## 6 geom_dtm_10m_hyd_fl5_L13 geom_10m_fl8_L12
## 7 geom_dtm_10m_hyd_fl5_L14 geom_10m_fl8_L150
## 8 geom_dtm_10m_hyd_fl5_L15 geom_10m_fl10_L15
## 9 geom_10m_fl4_L4 geom_10m_fl10_L14
## 10 geom_10m_fl4_L25 geom_dtm_10m_hyd_fl5_L8
## k 5
## 1 geom_10m_fl4_L10
## 2 geom_10m_fl8_L70
## 3 geom_10m_fl4_L110
## 4 geom_10m_fl4_L37
## 5 geom_10m_fl10_L70
## 6 geom_10m_fl10_L80
## 7 geom_10m_fl8_L3
## 8 geom_10m_fl10_L14
## 9 geom_10m_fl10_L10
## 10 geom_dtm_10m_hyd_fl5_L60
## [1] "10fold cv-error: 0.537037037037037"
## [1] "For predictors geom_10m_fl8_L16 AND geom_dtm_10m_hyd_fl5_L21"
##
## preds 2 3 4 5
## 2 23 10 7 1
## 3 0 0 0 0
## 4 10 13 28 16
## 5 0 0 0 0
## [1] "Kappa overall = 0.227215666582978"
## [1] "Tau overall = 0.296296296296296"
## [1] "mean quality = 0.20733969263381"
## [1] "The quality is 0.20733969263381"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = NaN"
## [1] "###################### WITH PREDICTORS from the FW SELECTION ###################"
## [1] "10fold cv-error: 0.62962962962963"
## [1] "For predictors geom_10m_fl8_L16 AND geom_dtm_10m_hyd_fl5_L21 AND geom_10m_fl10_L110 AND geom_10m_fl4_L8 AND geom_10m_fl2_L3 AND geom_10m_fl4_L19 AND geom_10m_fl1_L43 AND geom_10m_fl1_L44 AND geom_10m_fl1_L100 AND geom_10m_fl1_L80 AND geom_10m_fl8_L8 AND geom_10m_fl8_L80 AND geom_10m_fl10_L80 AND geom_10m_fl8_L90 AND geom_10m_fl10_L120 AND geom_10m_fl10_L26 AND geom_dtm_10m_hyd_fl5_L11 AND geom_10m_fl10_L40 AND geom_10m_fl10_L70 AND geom_10m_fl8_L12 AND geom_10m_fl4_L3 AND geom_dtm_10m_hyd_fl5_L27 AND geom_10m_fl4_L10 AND geom_dtm_10m_hyd_fl5_L30 AND geom_dtm_10m_hyd_fl5_L13 AND geom_dtm_10m_hyd_fl5_L14 AND geom_dtm_10m_hyd_fl5_L15 AND geom_10m_fl4_L4 AND geom_10m_fl4_L25 AND geom_10m_fl10_L150 AND geom_dtm_10m_hyd_fl5_L25 AND geom_dtm_10m_hyd_fl5_L10 AND geom_10m_fl10_L90 AND geom_10m_fl8_L150 AND geom_10m_fl10_L15 AND geom_10m_fl10_L14 AND geom_dtm_10m_hyd_fl5_L8 AND geom_10m_fl8_L70 AND geom_10m_fl4_L110 AND geom_10m_fl4_L37 AND geom_10m_fl8_L3 AND geom_10m_fl10_L10 AND geom_dtm_10m_hyd_fl5_L60"
##
## preds 2 3 4 5
## 2 21 9 8 8
## 3 0 0 0 0
## 4 12 14 27 9
## 5 0 0 0 0
## [1] "Kappa overall = 0.187562688064193"
## [1] "Tau overall = 0.259259259259259"
## [1] "mean quality = 0.186945812807882"
## [1] "The quality is 0.186945812807882"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = NaN"
## [1] "10fold cv-error: 0.787037037037037"
##
## preds 2 3 4 5
## 2 14 2 1 1
## 3 0 0 0 0
## 4 19 21 34 16
## 5 0 0 0 0
## [1] "Kappa overall = 0.181818181818182"
## [1] "Tau overall = 0.259259259259259"
## [1] "mean quality = 0.188001188001188"
## [1] "The quality is 0.188001188001188"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect

## [1] "######### Cramer's V = NaN"
## [1] "1a.3 - Habitat for soil organisms"
## [1] "Prediction error at end is: 0.694372294372294"
## [2] "Prediction error at end is: 0.722077922077922"
## [3] "Prediction error at end is: 0.712554112554113"
## [4] "Prediction error at end is: 0.721645021645022"
## [5] "Prediction error at end is: 0.722077922077922"
## [6] "Prediction error at end is: 0.731168831168831"
## [7] "Prediction error at end is: 0.721645021645022"
## [8] "Prediction error at end is: 0.721645021645022"
## [9] "Prediction error at end is: 0.721645021645022"
## [10] "Prediction error at end is: 0.721645021645022"
## k 1 k 2 k 3
## 1 geom_10m_fl10_L6 geom_10m_fl8_L40 geom_10m_fl2_L6
## 2 geom_10m_fl1_L11 geom_10m_fl2_L10 geom_10m_fl1_L5
## 3 geom_dtm_10m_hyd_fl5_L10 geom_10m_fl4_L140 geom_10m_fl2_L19
## 4 geom_dtm_10m_hyd_fl5_L110 geom_10m_fl1_L6 geom_10m_fl3_L9
## 5 geom_10m_fl1_L10 geom_10m_fl1_L5 geom_10m_fl4_L20
## 6 geom_10m_fl10_L5 geom_10m_fl10_L40 geom_10m_fl3_L6
## 7 geom_10m_fl10_L7 geom_10m_fl1_L3 geom_10m_fl3_L8
## 8 geom_10m_fl10_L40 geom_10m_fl1_L4 geom_10m_fl3_L11
## 9 geom_10m_fl8_L50 geom_10m_fl3_L5 geom_10m_fl1_L6
## 10 geom_10m_fl1_L6 geom_10m_fl3_L6 geom_10m_fl2_L10
## k 4 k 5
## 1 geom_10m_fl10_L11 geom_10m_fl10_L6
## 2 geom_10m_fl10_L8 geom_10m_fl10_L10
## 3 geom_10m_fl10_L10 geom_10m_fl10_L5
## 4 geom_10m_fl8_L4 geom_10m_fl10_L7
## 5 geom_10m_fl8_L5 geom_10m_fl10_L40
## 6 geom_10m_fl10_L3 geom_10m_fl10_L50
## 7 geom_10m_fl10_L6 geom_10m_fl10_L4
## 8 geom_10m_fl10_L12 geom_10m_fl10_L60
## 9 geom_10m_fl10_L13 geom_10m_fl10_L17
## 10 geom_10m_fl10_L15 geom_10m_fl10_L18
## [1] "10fold cv-error: 0.62037037037037"
## [1] "For predictors geom_10m_fl10_L6 AND geom_10m_fl1_L11"
##
## preds 1 2 3 4
## 1 0 0 0 0
## 2 24 27 5 8
## 3 0 7 21 13
## 4 0 0 0 3
## [1] "Kappa overall = 0.262754491017964"
## [1] "Tau overall = 0.296296296296296"
## [1] "mean quality = 0.24045085731782"
## [1] "The quality is 0.24045085731782"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = NaN"
## [1] "###################### WITH PREDICTORS from the FW SELECTION ###################"
## [1] "10fold cv-error: 0.685185185185185"
## [1] "For predictors geom_10m_fl10_L6 AND geom_10m_fl1_L11 AND geom_dtm_10m_hyd_fl5_L10 AND geom_dtm_10m_hyd_fl5_L110 AND geom_10m_fl1_L10 AND geom_10m_fl10_L5 AND geom_10m_fl10_L7 AND geom_10m_fl10_L40 AND geom_10m_fl8_L50 AND geom_10m_fl1_L6 AND geom_10m_fl8_L40 AND geom_10m_fl2_L10 AND geom_10m_fl4_L140 AND geom_10m_fl1_L5 AND geom_10m_fl1_L3 AND geom_10m_fl1_L4 AND geom_10m_fl3_L5 AND geom_10m_fl3_L6 AND geom_10m_fl2_L6 AND geom_10m_fl2_L19 AND geom_10m_fl3_L9 AND geom_10m_fl4_L20 AND geom_10m_fl3_L8 AND geom_10m_fl3_L11 AND geom_10m_fl10_L11 AND geom_10m_fl10_L8 AND geom_10m_fl10_L10 AND geom_10m_fl8_L4 AND geom_10m_fl8_L5 AND geom_10m_fl10_L3 AND geom_10m_fl10_L12 AND geom_10m_fl10_L13 AND geom_10m_fl10_L15 AND geom_10m_fl10_L50 AND geom_10m_fl10_L4 AND geom_10m_fl10_L60 AND geom_10m_fl10_L17 AND geom_10m_fl10_L18"
##
## preds 1 2 3 4
## 1 0 0 0 0
## 2 24 33 15 21
## 3 0 1 11 3
## 4 0 0 0 0
## [1] "Kappa overall = 0.14792899408284"
## [1] "Tau overall = 0.209876543209877"
## [1] "mean quality = 0.179432624113475"
## [1] "The quality is 0.179432624113475"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = NaN"
## [1] "10fold cv-error: 0.685185185185185"
##
## preds 1 2 3 4
## 1 0 0 0 0
## 2 24 34 26 24
## 3 0 0 0 0
## 4 0 0 0 0
## [1] "Kappa overall = 0"
## [1] "Tau overall = 0.0864197530864198"
## [1] "mean quality = 0.0787037037037037"
## [1] "The quality is 0.0787037037037037"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect

## [1] "######### Cramer's V = NaN"
## [1] "1a.4 - Habitat for crops"
## [1] "Prediction error at end is: 0.174891774891775"
## [2] "Prediction error at end is: 0.165800865800866"
## [3] "Prediction error at end is: 0.165800865800866"
## [4] "Prediction error at end is: 0.165800865800866"
## [5] "Prediction error at end is: 0.156709956709957"
## [6] "Prediction error at end is: 0.156709956709957"
## [7] "Prediction error at end is: 0.166233766233766"
## [8] "Prediction error at end is: 0.175324675324675"
## [9] "Prediction error at end is: 0.175324675324675"
## [10] "Prediction error at end is: 0.184415584415584"
## k 1 k 2
## 1 geom_10m_fl10_L6 geom_10m_fl10_L5
## 2 geom_10m_fl10_L7 geom_10m_fl10_L11
## 3 geom_10m_fl10_L5 geom_10m_fl10_L3
## 4 geom_10m_fl10_L8 geom_dtm_10m_hyd_fl5_L10
## 5 geom_10m_fl10_L9 geom_dtm_10m_hyd_fl5_L60
## 6 geom_10m_fl10_L60 geom_dtm_10m_hyd_fl5_L11
## 7 geom_dtm_10m_hyd_fl5_L60 geom_10m_fl10_L120
## 8 geom_dtm_10m_hyd_fl5_L42 geom_dtm_10m_hyd_fl5_L110
## 9 geom_dtm_10m_hyd_fl5_L43 geom_dtm_10m_hyd_fl5_L6
## 10 geom_dtm_10m_hyd_fl5_L44 geom_dtm_10m_hyd_fl5_L7
## k 3 k 4
## 1 geom_10m_fl10_L6 geom_10m_fl10_L6
## 2 geom_dtm_10m_hyd_fl5_L5 geom_10m_fl10_L70
## 3 geom_dtm_10m_hyd_fl5_L10 geom_dtm_10m_hyd_fl5_L60
## 4 geom_dtm_10m_hyd_fl5_L11 geom_dtm_10m_hyd_fl5_L120
## 5 geom_10m_fl10_L3 geom_dtm_10m_hyd_fl5_L130
## 6 geom_dtm_10m_hyd_fl5_L3 geom_10m_fl10_L3
## 7 geom_dtm_10m_hyd_fl5_L6 geom_10m_fl10_L7
## 8 geom_10m_fl10_L40 geom_10m_fl8_L3
## 9 geom_10m_fl10_L7 geom_10m_fl8_L5
## 10 geom_10m_fl10_L8 geom_10m_fl8_L4
## k 5
## 1 geom_10m_fl10_L6
## 2 geom_10m_fl10_L3
## 3 geom_dtm_10m_hyd_fl5_L6
## 4 geom_dtm_10m_hyd_fl5_L7
## 5 geom_dtm_10m_hyd_fl5_L10
## 6 geom_10m_fl10_L8
## 7 geom_dtm_10m_hyd_fl5_L3
## 8 geom_10m_fl10_L5
## 9 geom_dtm_10m_hyd_fl5_L5
## 10 geom_10m_fl8_L5
## [1] "10fold cv-error: 0.166666666666667"
## [1] "For predictors geom_10m_fl10_L6 AND geom_10m_fl10_L7"
##
## preds 3 4 5
## 3 0 0 0
## 4 7 58 4
## 5 1 4 34
## [1] "Kappa overall = 0.707317073170732"
## [1] "Tau overall = 0.777777777777778"
## [1] "mean quality = 0.52840607412127"
## [1] "The quality is 0.52840607412127"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = NaN"
## [1] "###################### WITH PREDICTORS from the FW SELECTION ###################"
## [1] "10fold cv-error: 0.175925925925926"
## [1] "For predictors geom_10m_fl10_L6 AND geom_10m_fl10_L7 AND geom_10m_fl10_L5 AND geom_10m_fl10_L8 AND geom_10m_fl10_L9 AND geom_10m_fl10_L60 AND geom_dtm_10m_hyd_fl5_L60 AND geom_dtm_10m_hyd_fl5_L42 AND geom_dtm_10m_hyd_fl5_L43 AND geom_dtm_10m_hyd_fl5_L44 AND geom_10m_fl10_L11 AND geom_10m_fl10_L3 AND geom_dtm_10m_hyd_fl5_L10 AND geom_dtm_10m_hyd_fl5_L11 AND geom_10m_fl10_L120 AND geom_dtm_10m_hyd_fl5_L110 AND geom_dtm_10m_hyd_fl5_L6 AND geom_dtm_10m_hyd_fl5_L7 AND geom_dtm_10m_hyd_fl5_L5 AND geom_dtm_10m_hyd_fl5_L3 AND geom_10m_fl10_L40 AND geom_10m_fl10_L70 AND geom_dtm_10m_hyd_fl5_L120 AND geom_dtm_10m_hyd_fl5_L130 AND geom_10m_fl8_L3 AND geom_10m_fl8_L5 AND geom_10m_fl8_L4"
##
## preds 3 4 5
## 3 0 0 0
## 4 7 58 4
## 5 1 4 34
## [1] "Kappa overall = 0.707317073170732"
## [1] "Tau overall = 0.777777777777778"
## [1] "mean quality = 0.52840607412127"
## [1] "The quality is 0.52840607412127"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = NaN"
## [1] "10fold cv-error: 0.416666666666667"
##
## preds 3 4 5
## 3 0 0 0
## 4 8 62 31
## 5 0 0 7
## [1] "Kappa overall = 0.179906542056075"
## [1] "Tau overall = 0.458333333333333"
## [1] "mean quality = 0.266023970818134"
## [1] "The quality is 0.266023970818134"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect

## [1] "######### Cramer's V = NaN"
## [1] "1c.1 - Average precipitation retention capacity"
## [1] "Prediction error at end is: 0.621645021645022"
## [2] "Prediction error at end is: 0.566666666666667"
## [3] "Prediction error at end is: 0.575757575757576"
## [4] "Prediction error at end is: 0.584848484848485"
## [5] "Prediction error at end is: 0.584848484848485"
## [6] "Prediction error at end is: 0.584848484848485"
## [7] "Prediction error at end is: 0.584848484848485"
## [8] "Prediction error at end is: 0.584848484848485"
## [9] "Prediction error at end is: 0.584848484848485"
## [10] "Prediction error at end is: 0.584848484848485"
## k 1 k 2 k 3 k 4
## 1 geom_10m_fl8_L3 geom_10m_fl1_L10 geom_10m_fl2_L6 geom_10m_fl1_L10
## 2 geom_10m_fl2_L6 geom_10m_fl1_L100 geom_10m_fl2_L7 geom_10m_fl1_L100
## 3 geom_10m_fl2_L7 geom_10m_fl1_L11 geom_10m_fl3_L7 geom_10m_fl1_L11
## 4 geom_10m_fl1_L3 geom_10m_fl1_L110 geom_10m_fl3_L6 geom_10m_fl1_L12
## 5 geom_10m_fl1_L120 geom_10m_fl1_L12 geom_10m_fl4_L6 geom_10m_fl1_L13
## 6 geom_10m_fl1_L130 geom_10m_fl1_L120 geom_10m_fl4_L7 geom_10m_fl1_L14
## 7 geom_10m_fl1_L140 geom_10m_fl1_L13 geom_10m_fl2_L5 geom_10m_fl1_L140
## 8 geom_10m_fl1_L150 geom_10m_fl1_L130 geom_10m_fl3_L5 geom_10m_fl1_L15
## 9 geom_10m_fl1_L16 geom_10m_fl1_L14 geom_10m_fl3_L8 geom_10m_fl1_L150
## 10 geom_10m_fl1_L17 geom_10m_fl1_L140 geom_10m_fl4_L5 geom_10m_fl1_L16
## k 5
## 1 geom_10m_fl2_L5
## 2 geom_10m_fl2_L6
## 3 geom_10m_fl2_L7
## 4 geom_10m_fl1_L5
## 5 geom_10m_fl1_L6
## 6 geom_10m_fl1_L7
## 7 geom_10m_fl2_L8
## 8 geom_10m_fl3_L5
## 9 geom_10m_fl3_L6
## 10 geom_10m_fl3_L7
## [1] "10fold cv-error: 0.583333333333333"
## [1] "For predictors geom_10m_fl8_L3 AND geom_10m_fl2_L6"
##
## preds 1 2 3 4 5
## 1 4 0 0 1 1
## 2 22 45 12 17 6
## 3 0 0 0 0 0
## 4 0 0 0 0 0
## 5 0 0 0 0 0
## [1] "Kappa overall = 0.0789245446660885"
## [1] "Tau overall = 0.31712962962963"
## [1] "mean quality = 0.116806722689076"
## [1] "The quality is 0.116806722689076"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = NaN"
## [1] "###################### WITH PREDICTORS from the FW SELECTION ###################"
## [1] "10fold cv-error: 0.583333333333333"
## [1] "For predictors geom_10m_fl8_L3 AND geom_10m_fl2_L6 AND geom_10m_fl2_L7 AND geom_10m_fl1_L3 AND geom_10m_fl1_L120 AND geom_10m_fl1_L130 AND geom_10m_fl1_L140 AND geom_10m_fl1_L150 AND geom_10m_fl1_L16 AND geom_10m_fl1_L17 AND geom_10m_fl1_L10 AND geom_10m_fl1_L100 AND geom_10m_fl1_L11 AND geom_10m_fl1_L110 AND geom_10m_fl1_L12 AND geom_10m_fl1_L13 AND geom_10m_fl1_L14 AND geom_10m_fl3_L7 AND geom_10m_fl3_L6 AND geom_10m_fl4_L6 AND geom_10m_fl4_L7 AND geom_10m_fl2_L5 AND geom_10m_fl3_L5 AND geom_10m_fl3_L8 AND geom_10m_fl4_L5 AND geom_10m_fl1_L15 AND geom_10m_fl1_L5 AND geom_10m_fl1_L6 AND geom_10m_fl1_L7 AND geom_10m_fl2_L8"
##
## preds 1 2 3 4 5
## 1 0 0 0 0 0
## 2 26 45 12 18 7
## 3 0 0 0 0 0
## 4 0 0 0 0 0
## 5 0 0 0 0 0
## [1] "Kappa overall = 0"
## [1] "Tau overall = 0.270833333333333"
## [1] "mean quality = 0.0833333333333333"
## [1] "The quality is 0.0833333333333333"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = NaN"
## [1] "10fold cv-error: 0.583333333333333"
##
## preds 1 2 3 4 5
## 1 0 0 0 0 0
## 2 26 45 12 18 7
## 3 0 0 0 0 0
## 4 0 0 0 0 0
## 5 0 0 0 0 0
## [1] "Kappa overall = 0"
## [1] "Tau overall = 0.270833333333333"
## [1] "mean quality = 0.0833333333333333"
## [1] "The quality is 0.0833333333333333"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect

## [1] "######### Cramer's V = NaN"
## [1] "1c.1 - Minimum precipitation retention capacity"
## [1] "Prediction error at end is: 0.813419913419913"
## [2] "Prediction error at end is: 0.804329004329004"
## [3] "Prediction error at end is: 0.822510822510823"
## [4] "Prediction error at end is: 0.795238095238095"
## [5] "Prediction error at end is: 0.804329004329004"
## [6] "Prediction error at end is: 0.804761904761905"
## [7] "Prediction error at end is: 0.814285714285714"
## [8] "Prediction error at end is: 0.795670995670996"
## [9] "Prediction error at end is: 0.795670995670996"
## [10] "Prediction error at end is: 0.795670995670996"
## k 1 k 2 k 3
## 1 geom_10m_fl10_L7 geom_10m_fl10_L7 geom_10m_fl10_L110
## 2 geom_dtm_10m_hyd_fl5_L5 geom_dtm_10m_hyd_fl5_L80 geom_10m_fl10_L150
## 3 geom_10m_fl10_L3 geom_dtm_10m_hyd_fl5_L150 geom_10m_fl3_L24
## 4 geom_10m_fl10_L90 geom_dtm_10m_hyd_fl5_L90 geom_10m_fl3_L25
## 5 geom_10m_fl8_L3 geom_dtm_10m_hyd_fl5_L8 geom_10m_fl10_L140
## 6 geom_10m_fl10_L4 geom_dtm_10m_hyd_fl5_L130 geom_10m_fl3_L20
## 7 geom_10m_fl10_L5 geom_10m_fl8_L5 geom_10m_fl3_L21
## 8 geom_10m_fl10_L6 geom_10m_fl1_L19 geom_10m_fl4_L17
## 9 geom_10m_fl8_L4 geom_10m_fl3_L10 geom_10m_fl3_L18
## 10 geom_dtm_10m_hyd_fl5_L4 geom_10m_fl3_L9 geom_10m_fl4_L18
## k 4 k 5
## 1 geom_10m_fl10_L90 geom_10m_fl3_L47
## 2 geom_10m_fl8_L5 geom_10m_fl3_L48
## 3 geom_10m_fl10_L5 geom_10m_fl3_L60
## 4 geom_10m_fl10_L40 geom_10m_fl2_L120
## 5 geom_10m_fl10_L150 geom_10m_fl3_L49
## 6 geom_10m_fl10_L140 geom_10m_fl2_L130
## 7 geom_10m_fl10_L100 geom_10m_fl1_L120
## 8 geom_10m_fl8_L3 geom_dtm_10m_hyd_fl5_L26
## 9 geom_10m_fl8_L4 geom_dtm_10m_hyd_fl5_L30
## 10 geom_10m_fl10_L4 geom_dtm_10m_hyd_fl5_L31
## [1] "10fold cv-error: 0.768518518518518"
## [1] "For predictors geom_10m_fl10_L7 AND geom_dtm_10m_hyd_fl5_L5"
##
## preds 1 2 3 4 5
## 1 0 0 0 0 0
## 2 4 20 15 15 4
## 3 0 0 0 0 0
## 4 7 6 6 11 13
## 5 1 0 1 0 5
## [1] "Kappa overall = 0.124718595227375"
## [1] "Tau overall = 0.166666666666667"
## [1] "mean quality = 0.142097701149425"
## [1] "The quality is 0.142097701149425"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = NaN"
## [1] "###################### WITH PREDICTORS from the FW SELECTION ###################"
## [1] "10fold cv-error: 0.805555555555556"
## [1] "For predictors geom_10m_fl10_L7 AND geom_dtm_10m_hyd_fl5_L5 AND geom_10m_fl10_L3 AND geom_10m_fl10_L90 AND geom_10m_fl8_L3 AND geom_10m_fl10_L4 AND geom_10m_fl10_L5 AND geom_10m_fl10_L6 AND geom_10m_fl8_L4 AND geom_dtm_10m_hyd_fl5_L4 AND geom_dtm_10m_hyd_fl5_L80 AND geom_dtm_10m_hyd_fl5_L150 AND geom_dtm_10m_hyd_fl5_L90 AND geom_dtm_10m_hyd_fl5_L8 AND geom_dtm_10m_hyd_fl5_L130 AND geom_10m_fl8_L5 AND geom_10m_fl1_L19 AND geom_10m_fl3_L10 AND geom_10m_fl3_L9 AND geom_10m_fl10_L110 AND geom_10m_fl10_L150 AND geom_10m_fl3_L24 AND geom_10m_fl3_L25 AND geom_10m_fl10_L140 AND geom_10m_fl3_L20 AND geom_10m_fl3_L21 AND geom_10m_fl4_L17 AND geom_10m_fl3_L18 AND geom_10m_fl4_L18 AND geom_10m_fl10_L40 AND geom_10m_fl10_L100 AND geom_10m_fl3_L47 AND geom_10m_fl3_L48 AND geom_10m_fl3_L60 AND geom_10m_fl2_L120 AND geom_10m_fl3_L49 AND geom_10m_fl2_L130 AND geom_10m_fl1_L120 AND geom_dtm_10m_hyd_fl5_L26 AND geom_dtm_10m_hyd_fl5_L30 AND geom_dtm_10m_hyd_fl5_L31"
##
## preds 1 2 3 4 5
## 1 0 0 0 0 0
## 2 4 19 9 9 9
## 3 0 0 0 0 0
## 4 8 7 13 17 13
## 5 0 0 0 0 0
## [1] "Kappa overall = 0.121951219512195"
## [1] "Tau overall = 0.166666666666667"
## [1] "mean quality = 0.117412935323383"
## [1] "The quality is 0.117412935323383"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = NaN"
## [1] "10fold cv-error: 0.851851851851852"
##
## preds 1 2 3 4 5
## 1 0 0 0 0 0
## 2 3 16 6 6 7
## 3 0 0 0 0 0
## 4 9 10 16 20 15
## 5 0 0 0 0 0
## [1] "Kappa overall = 0.121951219512195"
## [1] "Tau overall = 0.166666666666667"
## [1] "mean quality = 0.119298245614035"
## [1] "The quality is 0.119298245614035"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect

## [1] "######### Cramer's V = NaN"
## [1] "1c.2 - Retention capacity for heavy precipitation events"
## [1] "Prediction error at end is: 0.305627705627706"
## [2] "Prediction error at end is: 0.305627705627706"
## [3] "Prediction error at end is: 0.305627705627706"
## [4] "Prediction error at end is: 0.305627705627706"
## [5] "Prediction error at end is: 0.305627705627706"
## [6] "Prediction error at end is: 0.305627705627706"
## [7] "Prediction error at end is: 0.305627705627706"
## [8] "Prediction error at end is: 0.305627705627706"
## [9] "Prediction error at end is: 0.305627705627706"
## [10] "Prediction error at end is: 0.305627705627706"
## k 1 k 2 k 3 k 4
## 1 geom_10m_fl1_L10 geom_10m_fl1_L10 geom_10m_fl1_L10 geom_10m_fl1_L10
## 2 geom_10m_fl1_L100 geom_10m_fl1_L100 geom_10m_fl1_L100 geom_10m_fl1_L100
## 3 geom_10m_fl1_L11 geom_10m_fl1_L11 geom_10m_fl1_L11 geom_10m_fl1_L11
## 4 geom_10m_fl1_L110 geom_10m_fl1_L110 geom_10m_fl1_L110 geom_10m_fl1_L110
## 5 geom_10m_fl1_L12 geom_10m_fl1_L12 geom_10m_fl1_L12 geom_10m_fl1_L12
## 6 geom_10m_fl1_L120 geom_10m_fl1_L120 geom_10m_fl1_L120 geom_10m_fl1_L120
## 7 geom_10m_fl1_L13 geom_10m_fl1_L13 geom_10m_fl1_L13 geom_10m_fl1_L13
## 8 geom_10m_fl1_L130 geom_10m_fl1_L130 geom_10m_fl1_L130 geom_10m_fl1_L130
## 9 geom_10m_fl1_L14 geom_10m_fl1_L14 geom_10m_fl1_L14 geom_10m_fl1_L14
## 10 geom_10m_fl1_L140 geom_10m_fl1_L140 geom_10m_fl1_L140 geom_10m_fl1_L140
## k 5
## 1 geom_10m_fl1_L10
## 2 geom_10m_fl1_L100
## 3 geom_10m_fl1_L11
## 4 geom_10m_fl1_L110
## 5 geom_10m_fl1_L12
## 6 geom_10m_fl1_L120
## 7 geom_10m_fl1_L13
## 8 geom_10m_fl1_L130
## 9 geom_10m_fl1_L14
## 10 geom_10m_fl1_L140
## [1] "10fold cv-error: 0.305555555555556"
## [1] "For predictors geom_10m_fl1_L10 AND geom_10m_fl1_L100"
##
## preds 1 2 3 4 5
## 1 75 11 6 8 8
## 2 0 0 0 0 0
## 3 0 0 0 0 0
## 4 0 0 0 0 0
## 5 0 0 0 0 0
## [1] "Kappa overall = 0"
## [1] "Tau overall = 0.618055555555555"
## [1] "mean quality = 0.138888888888889"
## [1] "The quality is 0.138888888888889"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = NaN"
## [1] "###################### WITH PREDICTORS from the FW SELECTION ###################"
## [1] "10fold cv-error: 0.305555555555556"
## [1] "For predictors geom_10m_fl1_L10 AND geom_10m_fl1_L100 AND geom_10m_fl1_L11 AND geom_10m_fl1_L110 AND geom_10m_fl1_L12 AND geom_10m_fl1_L120 AND geom_10m_fl1_L13 AND geom_10m_fl1_L130 AND geom_10m_fl1_L14 AND geom_10m_fl1_L140"
##
## preds 1 2 3 4 5
## 1 75 11 6 8 8
## 2 0 0 0 0 0
## 3 0 0 0 0 0
## 4 0 0 0 0 0
## 5 0 0 0 0 0
## [1] "Kappa overall = 0"
## [1] "Tau overall = 0.618055555555555"
## [1] "mean quality = 0.138888888888889"
## [1] "The quality is 0.138888888888889"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = NaN"
## [1] "10fold cv-error: 0.305555555555556"
##
## preds 1 2 3 4 5
## 1 75 11 6 8 8
## 2 0 0 0 0 0
## 3 0 0 0 0 0
## 4 0 0 0 0 0
## 5 0 0 0 0 0
## [1] "Kappa overall = 0"
## [1] "Tau overall = 0.618055555555555"
## [1] "mean quality = 0.138888888888889"
## [1] "The quality is 0.138888888888889"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect

## [1] "######### Cramer's V = NaN"
## [1] "1c.3 - groundwater reformation rate"
## [1] "Prediction error at end is: 0.666233766233766"
## [2] "Prediction error at end is: 0.657575757575758"
## [3] "Prediction error at end is: 0.667099567099567"
## [4] "Prediction error at end is: 0.676623376623377"
## [5] "Prediction error at end is: 0.638528138528139"
## [6] "Prediction error at end is: 0.638528138528139"
## [7] "Prediction error at end is: 0.638528138528139"
## [8] "Prediction error at end is: 0.638528138528139"
## [9] "Prediction error at end is: 0.638528138528139"
## [10] "Prediction error at end is: 0.647619047619048"
## k 1 k 2 k 3
## 1 geom_10m_fl8_L3 geom_10m_fl3_L70 geom_10m_fl1_L10
## 2 geom_10m_fl8_L13 geom_10m_fl4_L90 geom_10m_fl1_L100
## 3 geom_10m_fl8_L14 geom_10m_fl4_L100 geom_10m_fl1_L11
## 4 geom_10m_fl1_L10 geom_10m_fl3_L60 geom_10m_fl1_L110
## 5 geom_10m_fl1_L100 geom_10m_fl4_L120 geom_10m_fl1_L12
## 6 geom_10m_fl1_L11 geom_10m_fl4_L130 geom_10m_fl1_L120
## 7 geom_10m_fl1_L110 geom_10m_fl4_L140 geom_10m_fl1_L13
## 8 geom_10m_fl1_L12 geom_10m_fl4_L150 geom_10m_fl1_L130
## 9 geom_10m_fl1_L120 geom_10m_fl4_L80 geom_10m_fl1_L14
## 10 geom_10m_fl1_L13 geom_dtm_10m_hyd_fl5_L100 geom_10m_fl1_L140
## k 4 k 5
## 1 geom_10m_fl10_L10 geom_10m_fl10_L6
## 2 geom_10m_fl10_L15 geom_10m_fl10_L7
## 3 geom_dtm_10m_hyd_fl5_L100 geom_10m_fl10_L5
## 4 geom_dtm_10m_hyd_fl5_L60 geom_10m_fl8_L3
## 5 geom_dtm_10m_hyd_fl5_L41 geom_10m_fl8_L5
## 6 geom_dtm_10m_hyd_fl5_L42 geom_10m_fl8_L4
## 7 geom_dtm_10m_hyd_fl5_L43 geom_10m_fl10_L4
## 8 geom_dtm_10m_hyd_fl5_L44 geom_10m_fl10_L3
## 9 geom_dtm_10m_hyd_fl5_L45 geom_10m_fl10_L8
## 10 geom_dtm_10m_hyd_fl5_L70 geom_10m_fl10_L9
## [1] "10fold cv-error: 0.675925925925926"
## [1] "For predictors geom_10m_fl8_L3 AND geom_10m_fl8_L13"
##
## preds 1 2 3 4 5
## 1 0 0 0 0 0
## 2 11 30 13 7 5
## 3 0 0 0 0 0
## 4 0 0 0 0 0
## 5 3 9 1 12 17
## [1] "Kappa overall = 0.193240264511389"
## [1] "Tau overall = 0.293981481481481"
## [1] "mean quality = 0.152340425531915"
## [1] "The quality is 0.152340425531915"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = NaN"
## [1] "###################### WITH PREDICTORS from the FW SELECTION ###################"
## [1] "10fold cv-error: 0.638888888888889"
## [1] "For predictors geom_10m_fl8_L3 AND geom_10m_fl8_L13 AND geom_10m_fl8_L14 AND geom_10m_fl1_L10 AND geom_10m_fl1_L100 AND geom_10m_fl1_L11 AND geom_10m_fl1_L110 AND geom_10m_fl1_L12 AND geom_10m_fl1_L120 AND geom_10m_fl1_L13 AND geom_10m_fl3_L70 AND geom_10m_fl4_L90 AND geom_10m_fl4_L100 AND geom_10m_fl3_L60 AND geom_10m_fl4_L120 AND geom_10m_fl4_L130 AND geom_10m_fl4_L140 AND geom_10m_fl4_L150 AND geom_10m_fl4_L80 AND geom_dtm_10m_hyd_fl5_L100 AND geom_10m_fl1_L130 AND geom_10m_fl1_L14 AND geom_10m_fl1_L140 AND geom_10m_fl10_L10 AND geom_10m_fl10_L15 AND geom_dtm_10m_hyd_fl5_L60 AND geom_dtm_10m_hyd_fl5_L41 AND geom_dtm_10m_hyd_fl5_L42 AND geom_dtm_10m_hyd_fl5_L43 AND geom_dtm_10m_hyd_fl5_L44 AND geom_dtm_10m_hyd_fl5_L45 AND geom_dtm_10m_hyd_fl5_L70 AND geom_10m_fl10_L6 AND geom_10m_fl10_L7 AND geom_10m_fl10_L5 AND geom_10m_fl8_L5 AND geom_10m_fl8_L4 AND geom_10m_fl10_L4 AND geom_10m_fl10_L3 AND geom_10m_fl10_L8 AND geom_10m_fl10_L9"
##
## preds 1 2 3 4 5
## 1 0 0 0 0 0
## 2 14 39 14 19 22
## 3 0 0 0 0 0
## 4 0 0 0 0 0
## 5 0 0 0 0 0
## [1] "Kappa overall = 0"
## [1] "Tau overall = 0.201388888888889"
## [1] "mean quality = 0.0722222222222222"
## [1] "The quality is 0.0722222222222222"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = NaN"
## [1] "10fold cv-error: 0.638888888888889"
##
## preds 1 2 3 4 5
## 1 0 0 0 0 0
## 2 14 39 14 19 22
## 3 0 0 0 0 0
## 4 0 0 0 0 0
## 5 0 0 0 0 0
## [1] "Kappa overall = 0"
## [1] "Tau overall = 0.201388888888889"
## [1] "mean quality = 0.0722222222222222"
## [1] "The quality is 0.0722222222222222"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect

## [1] "######### Cramer's V = NaN"
## [1] "1c.4 - Potential for providing nutrients for plants"
## [1] "Prediction error at end is: 0.435064935064935"
## [2] "Prediction error at end is: 0.435064935064935"
## [3] "Prediction error at end is: 0.435497835497835"
## [4] "Prediction error at end is: 0.426406926406926"
## [5] "Prediction error at end is: 0.416883116883117"
## [6] "Prediction error at end is: 0.416883116883117"
## [7] "Prediction error at end is: 0.416883116883117"
## [8] "Prediction error at end is: 0.426406926406926"
## [9] "Prediction error at end is: 0.426406926406926"
## [10] "Prediction error at end is: 0.426406926406926"
## k 1 k 2 k 3 k 4
## 1 geom_10m_fl10_L11 geom_10m_fl1_L10 geom_10m_fl10_L10 geom_10m_fl8_L3
## 2 geom_10m_fl10_L12 geom_10m_fl1_L100 geom_10m_fl10_L17 geom_10m_fl10_L21
## 3 geom_10m_fl10_L14 geom_10m_fl1_L11 geom_10m_fl10_L25 geom_10m_fl10_L25
## 4 geom_10m_fl1_L100 geom_10m_fl1_L110 geom_10m_fl10_L3 geom_10m_fl10_L22
## 5 geom_10m_fl1_L110 geom_10m_fl1_L12 geom_10m_fl8_L3 geom_10m_fl8_L130
## 6 geom_10m_fl1_L120 geom_10m_fl1_L120 geom_10m_fl8_L4 geom_10m_fl8_L140
## 7 geom_10m_fl1_L13 geom_10m_fl1_L13 geom_10m_fl10_L23 geom_10m_fl8_L150
## 8 geom_10m_fl1_L130 geom_10m_fl1_L130 geom_10m_fl10_L24 geom_10m_fl8_L110
## 9 geom_10m_fl1_L14 geom_10m_fl1_L14 geom_10m_fl10_L26 geom_10m_fl10_L15
## 10 geom_10m_fl1_L140 geom_10m_fl1_L140 geom_10m_fl10_L27 geom_10m_fl10_L11
## k 5
## 1 geom_10m_fl1_L10
## 2 geom_10m_fl1_L100
## 3 geom_10m_fl1_L11
## 4 geom_10m_fl1_L110
## 5 geom_10m_fl1_L12
## 6 geom_10m_fl1_L120
## 7 geom_10m_fl1_L13
## 8 geom_10m_fl1_L130
## 9 geom_10m_fl1_L14
## 10 geom_10m_fl1_L140
## [1] "10fold cv-error: 0.435185185185185"
## [1] "For predictors geom_10m_fl10_L11 AND geom_10m_fl10_L12"
##
## preds 1 3 5
## 1 53 7 12
## 3 0 0 0
## 5 12 4 20
## [1] "Kappa overall = 0.351851851851852"
## [1] "Tau overall = 0.513888888888889"
## [1] "mean quality = 0.349206349206349"
## [1] "The quality is 0.349206349206349"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = NaN"
## [1] "###################### WITH PREDICTORS from the FW SELECTION ###################"
## [1] "10fold cv-error: 0.398148148148148"
## [1] "For predictors geom_10m_fl10_L11 AND geom_10m_fl10_L12 AND geom_10m_fl10_L14 AND geom_10m_fl1_L100 AND geom_10m_fl1_L110 AND geom_10m_fl1_L120 AND geom_10m_fl1_L13 AND geom_10m_fl1_L130 AND geom_10m_fl1_L14 AND geom_10m_fl1_L140 AND geom_10m_fl1_L10 AND geom_10m_fl1_L11 AND geom_10m_fl1_L12 AND geom_10m_fl10_L10 AND geom_10m_fl10_L17 AND geom_10m_fl10_L25 AND geom_10m_fl10_L3 AND geom_10m_fl8_L3 AND geom_10m_fl8_L4 AND geom_10m_fl10_L23 AND geom_10m_fl10_L24 AND geom_10m_fl10_L26 AND geom_10m_fl10_L27 AND geom_10m_fl10_L21 AND geom_10m_fl10_L22 AND geom_10m_fl8_L130 AND geom_10m_fl8_L140 AND geom_10m_fl8_L150 AND geom_10m_fl8_L110 AND geom_10m_fl10_L15"
##
## preds 1 3 5
## 1 65 11 32
## 3 0 0 0
## 5 0 0 0
## [1] "Kappa overall = 0"
## [1] "Tau overall = 0.402777777777778"
## [1] "mean quality = 0.200617283950617"
## [1] "The quality is 0.200617283950617"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = NaN"
## [1] "10fold cv-error: 0.398148148148148"
##
## preds 1 3 5
## 1 65 11 32
## 3 0 0 0
## 5 0 0 0
## [1] "Kappa overall = 0"
## [1] "Tau overall = 0.402777777777778"
## [1] "mean quality = 0.200617283950617"
## [1] "The quality is 0.200617283950617"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect

## [1] "######### Cramer's V = NaN"
## [1] "1c.5 - Potential as a CO2 sink"
## [1] "Prediction error at end is: 0.417316017316017"
## [2] "Prediction error at end is: 0.445887445887446"
## [3] "Prediction error at end is: 0.445887445887446"
## [4] "Prediction error at end is: 0.518614718614719"
## [5] "Prediction error at end is: 0.537229437229437"
## [6] "Prediction error at end is: 0.537229437229437"
## [7] "Prediction error at end is: 0.537229437229437"
## [8] "Prediction error at end is: 0.527705627705628"
## [9] "Prediction error at end is: 0.537229437229437"
## [10] "Prediction error at end is: 0.537229437229437"
## k 1 k 2 k 3
## 1 geom_10m_fl10_L10 geom_10m_fl10_L10 geom_10m_fl10_L11
## 2 geom_10m_fl10_L11 geom_10m_fl10_L11 geom_10m_fl10_L12
## 3 geom_10m_fl10_L12 geom_dtm_10m_hyd_fl5_L34 geom_10m_fl10_L7
## 4 geom_10m_fl10_L110 geom_10m_fl3_L33 geom_10m_fl1_L7
## 5 geom_dtm_10m_hyd_fl5_L6 geom_10m_fl2_L19 geom_10m_fl3_L16
## 6 geom_10m_fl10_L120 geom_10m_fl3_L23 geom_10m_fl10_L40
## 7 geom_10m_fl10_L130 geom_10m_fl3_L24 geom_10m_fl1_L100
## 8 geom_dtm_10m_hyd_fl5_L36 geom_10m_fl3_L27 geom_10m_fl10_L6
## 9 geom_dtm_10m_hyd_fl5_L37 geom_10m_fl3_L28 geom_10m_fl10_L27
## 10 geom_dtm_10m_hyd_fl5_L38 geom_10m_fl1_L11 geom_10m_fl10_L13
## k 4 k 5
## 1 geom_10m_fl8_L4 geom_10m_fl10_L10
## 2 geom_10m_fl8_L40 geom_10m_fl8_L16
## 3 geom_10m_fl8_L50 geom_10m_fl8_L50
## 4 geom_10m_fl10_L6 geom_10m_fl8_L7
## 5 geom_10m_fl1_L33 geom_10m_fl10_L27
## 6 geom_10m_fl8_L60 geom_10m_fl10_L4
## 7 geom_10m_fl10_L5 geom_10m_fl10_L3
## 8 geom_10m_fl8_L5 geom_10m_fl1_L150
## 9 geom_10m_fl10_L4 geom_10m_fl2_L150
## 10 geom_10m_fl10_L7 geom_10m_fl3_L150
## [1] "10fold cv-error: 0.407407407407407"
## [1] "For predictors geom_10m_fl10_L10 AND geom_10m_fl10_L11"
##
## preds 1 2 3 4 5
## 1 41 0 2 9 2
## 2 0 0 0 0 0
## 3 0 0 0 0 0
## 4 10 1 16 24 3
## 5 0 0 0 0 0
## [1] "Kappa overall = 0.348484848484848"
## [1] "Tau overall = 0.502314814814815"
## [1] "mean quality = 0.204315476190476"
## [1] "The quality is 0.204315476190476"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = NaN"
## [1] "###################### WITH PREDICTORS from the FW SELECTION ###################"
## [1] "10fold cv-error: 0.527777777777778"
## [1] "For predictors geom_10m_fl10_L10 AND geom_10m_fl10_L11 AND geom_10m_fl10_L12 AND geom_10m_fl10_L110 AND geom_dtm_10m_hyd_fl5_L6 AND geom_10m_fl10_L120 AND geom_10m_fl10_L130 AND geom_dtm_10m_hyd_fl5_L36 AND geom_dtm_10m_hyd_fl5_L37 AND geom_dtm_10m_hyd_fl5_L38 AND geom_dtm_10m_hyd_fl5_L34 AND geom_10m_fl3_L33 AND geom_10m_fl2_L19 AND geom_10m_fl3_L23 AND geom_10m_fl3_L24 AND geom_10m_fl3_L27 AND geom_10m_fl3_L28 AND geom_10m_fl1_L11 AND geom_10m_fl10_L7 AND geom_10m_fl1_L7 AND geom_10m_fl3_L16 AND geom_10m_fl10_L40 AND geom_10m_fl1_L100 AND geom_10m_fl10_L6 AND geom_10m_fl10_L27 AND geom_10m_fl10_L13 AND geom_10m_fl8_L4 AND geom_10m_fl8_L40 AND geom_10m_fl8_L50 AND geom_10m_fl1_L33 AND geom_10m_fl8_L60 AND geom_10m_fl10_L5 AND geom_10m_fl8_L5 AND geom_10m_fl10_L4 AND geom_10m_fl8_L16 AND geom_10m_fl8_L7 AND geom_10m_fl10_L3 AND geom_10m_fl1_L150 AND geom_10m_fl2_L150 AND geom_10m_fl3_L150"
##
## preds 1 2 3 4 5
## 1 51 1 18 33 5
## 2 0 0 0 0 0
## 3 0 0 0 0 0
## 4 0 0 0 0 0
## 5 0 0 0 0 0
## [1] "Kappa overall = 0"
## [1] "Tau overall = 0.340277777777778"
## [1] "mean quality = 0.0944444444444444"
## [1] "The quality is 0.0944444444444444"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = NaN"
## [1] "10fold cv-error: 0.527777777777778"
##
## preds 1 2 3 4 5
## 1 51 1 18 33 5
## 2 0 0 0 0 0
## 3 0 0 0 0 0
## 4 0 0 0 0 0
## 5 0 0 0 0 0
## [1] "Kappa overall = 0"
## [1] "Tau overall = 0.340277777777778"
## [1] "mean quality = 0.0944444444444444"
## [1] "The quality is 0.0944444444444444"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect

## [1] "######### Cramer's V = NaN"
## [1] "1d.1 - Potential for retention of heavy metals"
## [1] "Prediction error at end is: 0.398701298701299"
## [2] "Prediction error at end is: 0.398701298701299"
## [3] "Prediction error at end is: 0.398701298701299"
## [4] "Prediction error at end is: 0.425974025974026"
## [5] "Prediction error at end is: 0.407359307359307"
## [6] "Prediction error at end is: 0.435064935064935"
## [7] "Prediction error at end is: 0.435064935064935"
## [8] "Prediction error at end is: 0.444155844155844"
## [9] "Prediction error at end is: 0.444155844155844"
## [10] "Prediction error at end is: 0.444155844155844"
## k 1 k 2
## 1 geom_10m_fl8_L8 geom_10m_fl10_L8
## 2 geom_10m_fl10_L10 geom_dtm_10m_hyd_fl5_L6
## 3 geom_10m_fl10_L3 geom_10m_fl10_L90
## 4 geom_dtm_10m_hyd_fl5_L110 geom_10m_fl10_L10
## 5 geom_dtm_10m_hyd_fl5_L13 geom_10m_fl8_L4
## 6 geom_dtm_10m_hyd_fl5_L5 geom_10m_fl10_L5
## 7 geom_10m_fl8_L5 geom_10m_fl8_L60
## 8 geom_10m_fl10_L5 geom_10m_fl8_L50
## 9 geom_dtm_10m_hyd_fl5_L37 geom_10m_fl8_L40
## 10 geom_10m_fl10_L4 geom_10m_fl8_L5
## k 3 k 4
## 1 geom_10m_fl10_L7 geom_10m_fl8_L6
## 2 geom_10m_fl10_L8 geom_10m_fl8_L7
## 3 geom_dtm_10m_hyd_fl5_L6 geom_dtm_10m_hyd_fl5_L3
## 4 geom_dtm_10m_hyd_fl5_L29 geom_dtm_10m_hyd_fl5_L5
## 5 geom_dtm_10m_hyd_fl5_L42 geom_dtm_10m_hyd_fl5_L39
## 6 geom_dtm_10m_hyd_fl5_L17 geom_dtm_10m_hyd_fl5_L12
## 7 geom_10m_fl10_L70 geom_dtm_10m_hyd_fl5_L100
## 8 geom_dtm_10m_hyd_fl5_L7 geom_10m_fl10_L140
## 9 geom_10m_fl10_L80 geom_dtm_10m_hyd_fl5_L42
## 10 geom_dtm_10m_hyd_fl5_L5 geom_10m_fl8_L9
## k 5
## 1 geom_10m_fl8_L4
## 2 geom_10m_fl10_L27
## 3 geom_10m_fl10_L15
## 4 geom_10m_fl10_L80
## 5 geom_dtm_10m_hyd_fl5_L110
## 6 geom_10m_fl8_L5
## 7 geom_dtm_10m_hyd_fl5_L130
## 8 geom_10m_fl8_L6
## 9 geom_10m_fl10_L7
## 10 geom_10m_fl8_L3
## [1] "10fold cv-error: 0.388888888888889"
## [1] "For predictors geom_10m_fl8_L8 AND geom_10m_fl10_L10"
##
## preds 1 2 3 4 5
## 1 33 2 6 2 5
## 2 0 0 0 0 0
## 3 0 0 0 0 0
## 4 0 0 0 0 0
## 5 9 5 4 5 37
## [1] "Kappa overall = 0.424242424242424"
## [1] "Tau overall = 0.560185185185185"
## [1] "mean quality = 0.229635627530364"
## [1] "The quality is 0.229635627530364"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = NaN"
## [1] "###################### WITH PREDICTORS from the FW SELECTION ###################"
## [1] "10fold cv-error: 0.435185185185185"
## [1] "For predictors geom_10m_fl8_L8 AND geom_10m_fl10_L10 AND geom_10m_fl10_L3 AND geom_dtm_10m_hyd_fl5_L110 AND geom_dtm_10m_hyd_fl5_L13 AND geom_dtm_10m_hyd_fl5_L5 AND geom_10m_fl8_L5 AND geom_10m_fl10_L5 AND geom_dtm_10m_hyd_fl5_L37 AND geom_10m_fl10_L4 AND geom_10m_fl10_L8 AND geom_dtm_10m_hyd_fl5_L6 AND geom_10m_fl10_L90 AND geom_10m_fl8_L4 AND geom_10m_fl8_L60 AND geom_10m_fl8_L50 AND geom_10m_fl8_L40 AND geom_10m_fl10_L7 AND geom_dtm_10m_hyd_fl5_L29 AND geom_dtm_10m_hyd_fl5_L42 AND geom_dtm_10m_hyd_fl5_L17 AND geom_10m_fl10_L70 AND geom_dtm_10m_hyd_fl5_L7 AND geom_10m_fl10_L80 AND geom_10m_fl8_L6 AND geom_10m_fl8_L7 AND geom_dtm_10m_hyd_fl5_L3 AND geom_dtm_10m_hyd_fl5_L39 AND geom_dtm_10m_hyd_fl5_L12 AND geom_dtm_10m_hyd_fl5_L100 AND geom_10m_fl10_L140 AND geom_10m_fl8_L9 AND geom_10m_fl10_L27 AND geom_10m_fl10_L15 AND geom_dtm_10m_hyd_fl5_L130 AND geom_10m_fl8_L3"
##
## preds 1 2 3 4 5
## 1 37 3 8 3 13
## 2 0 0 0 0 0
## 3 0 0 0 0 0
## 4 0 0 0 0 0
## 5 5 4 2 4 29
## [1] "Kappa overall = 0.363636363636364"
## [1] "Tau overall = 0.513888888888889"
## [1] "mean quality = 0.209000762776506"
## [1] "The quality is 0.209000762776506"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = NaN"
## [1] "10fold cv-error: 0.592592592592593"
##
## preds 1 2 3 4 5
## 1 32 2 6 3 8
## 2 0 0 0 0 0
## 3 0 0 0 0 0
## 4 0 0 0 0 0
## 5 10 5 4 4 34
## [1] "Kappa overall = 0.363636363636364"
## [1] "Tau overall = 0.513888888888889"
## [1] "mean quality = 0.20953341740227"
## [1] "The quality is 0.20953341740227"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect

## [1] "######### Cramer's V = NaN"
## [1] "1d.2 - Potential for transforming organic contaminants"
## [1] "Prediction error at end is: 0.647619047619048"
## [2] "Prediction error at end is: 0.647619047619048"
## [3] "Prediction error at end is: 0.665800865800866"
## [4] "Prediction error at end is: 0.665800865800866"
## [5] "Prediction error at end is: 0.665800865800866"
## [6] "Prediction error at end is: 0.674891774891775"
## [7] "Prediction error at end is: 0.647186147186147"
## [8] "Prediction error at end is: 0.656277056277056"
## [9] "Prediction error at end is: 0.656277056277056"
## [10] "Prediction error at end is: 0.656277056277056"
## k 1 k 2 k 3
## 1 geom_10m_fl8_L9 geom_10m_fl8_L9 geom_10m_fl8_L10
## 2 geom_dtm_10m_hyd_fl5_L6 geom_dtm_10m_hyd_fl5_L8 geom_10m_fl8_L23
## 3 geom_10m_fl10_L100 geom_dtm_10m_hyd_fl5_L29 geom_10m_fl10_L50
## 4 geom_10m_fl10_L3 geom_10m_fl1_L3 geom_10m_fl1_L100
## 5 geom_10m_fl10_L23 geom_10m_fl1_L4 geom_10m_fl1_L110
## 6 geom_dtm_10m_hyd_fl5_L42 geom_10m_fl4_L6 geom_10m_fl1_L140
## 7 geom_dtm_10m_hyd_fl5_L43 geom_10m_fl4_L7 geom_10m_fl1_L150
## 8 geom_dtm_10m_hyd_fl5_L44 geom_10m_fl4_L8 geom_10m_fl1_L22
## 9 geom_dtm_10m_hyd_fl5_L45 geom_10m_fl1_L100 geom_10m_fl1_L80
## 10 geom_dtm_10m_hyd_fl5_L5 geom_10m_fl1_L110 geom_10m_fl1_L9
## k 4 k 5
## 1 geom_10m_fl8_L4 geom_10m_fl8_L10
## 2 geom_10m_fl10_L13 geom_10m_fl8_L11
## 3 geom_10m_fl10_L60 geom_10m_fl8_L7
## 4 geom_10m_fl10_L6 geom_10m_fl8_L5
## 5 geom_10m_fl10_L7 geom_10m_fl8_L8
## 6 geom_10m_fl10_L22 geom_10m_fl8_L50
## 7 geom_10m_fl10_L21 geom_10m_fl8_L40
## 8 geom_10m_fl10_L5 geom_10m_fl8_L150
## 9 geom_10m_fl8_L80 geom_10m_fl8_L130
## 10 geom_10m_fl10_L90 geom_10m_fl8_L140
## [1] "10fold cv-error: 0.574074074074074"
## [1] "For predictors geom_10m_fl8_L9 AND geom_dtm_10m_hyd_fl5_L6"
##
## preds 1 2 3 4 5
## 1 0 0 0 0 0
## 2 0 0 0 0 0
## 3 8 14 16 2 5
## 4 0 0 0 0 0
## 5 2 8 12 7 34
## [1] "Kappa overall = 0.211778029445074"
## [1] "Tau overall = 0.328703703703704"
## [1] "mean quality = 0.156140350877193"
## [1] "The quality is 0.156140350877193"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = NaN"
## [1] "###################### WITH PREDICTORS from the FW SELECTION ###################"
## [1] "10fold cv-error: 0.638888888888889"
## [1] "For predictors geom_10m_fl8_L9 AND geom_dtm_10m_hyd_fl5_L6 AND geom_10m_fl10_L100 AND geom_10m_fl10_L3 AND geom_10m_fl10_L23 AND geom_dtm_10m_hyd_fl5_L42 AND geom_dtm_10m_hyd_fl5_L43 AND geom_dtm_10m_hyd_fl5_L44 AND geom_dtm_10m_hyd_fl5_L45 AND geom_dtm_10m_hyd_fl5_L5 AND geom_dtm_10m_hyd_fl5_L8 AND geom_dtm_10m_hyd_fl5_L29 AND geom_10m_fl1_L3 AND geom_10m_fl1_L4 AND geom_10m_fl4_L6 AND geom_10m_fl4_L7 AND geom_10m_fl4_L8 AND geom_10m_fl1_L100 AND geom_10m_fl1_L110 AND geom_10m_fl8_L10 AND geom_10m_fl8_L23 AND geom_10m_fl10_L50 AND geom_10m_fl1_L140 AND geom_10m_fl1_L150 AND geom_10m_fl1_L22 AND geom_10m_fl1_L80 AND geom_10m_fl1_L9 AND geom_10m_fl8_L4 AND geom_10m_fl10_L13 AND geom_10m_fl10_L60 AND geom_10m_fl10_L6 AND geom_10m_fl10_L7 AND geom_10m_fl10_L22 AND geom_10m_fl10_L21 AND geom_10m_fl10_L5 AND geom_10m_fl8_L80 AND geom_10m_fl10_L90 AND geom_10m_fl8_L11 AND geom_10m_fl8_L7 AND geom_10m_fl8_L5 AND geom_10m_fl8_L8 AND geom_10m_fl8_L50 AND geom_10m_fl8_L40 AND geom_10m_fl8_L150 AND geom_10m_fl8_L130 AND geom_10m_fl8_L140"
##
## preds 1 2 3 4 5
## 1 0 0 0 0 0
## 2 0 0 0 0 0
## 3 0 0 0 0 0
## 4 0 0 0 0 0
## 5 10 22 28 9 39
## [1] "Kappa overall = 0"
## [1] "Tau overall = 0.201388888888889"
## [1] "mean quality = 0.0722222222222222"
## [1] "The quality is 0.0722222222222222"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = NaN"
## [1] "10fold cv-error: 0.638888888888889"
##
## preds 1 2 3 4 5
## 1 0 0 0 0 0
## 2 0 0 0 0 0
## 3 0 0 0 0 0
## 4 0 0 0 0 0
## 5 10 22 28 9 39
## [1] "Kappa overall = 0"
## [1] "Tau overall = 0.201388888888889"
## [1] "mean quality = 0.0722222222222222"
## [1] "The quality is 0.0722222222222222"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect

## [1] "######### Cramer's V = NaN"
## [1] "1d.3 - Potential as filter and buffer for organic contaminants"
## [1] "Prediction error at end is: 0.0372294372294372"
## [2] "Prediction error at end is: 0.0372294372294372"
## [3] "Prediction error at end is: 0.0372294372294372"
## [4] "Prediction error at end is: 0.0372294372294372"
## [5] "Prediction error at end is: 0.0372294372294372"
## [6] "Prediction error at end is: 0.0372294372294372"
## [7] "Prediction error at end is: 0.0372294372294372"
## [8] "Prediction error at end is: 0.0372294372294372"
## [9] "Prediction error at end is: 0.0372294372294372"
## [10] "Prediction error at end is: 0.0372294372294372"
## k 1 k 2 k 3 k 4
## 1 geom_10m_fl1_L10 geom_10m_fl1_L10 geom_10m_fl1_L10 geom_10m_fl1_L10
## 2 geom_10m_fl1_L100 geom_10m_fl1_L100 geom_10m_fl1_L100 geom_10m_fl1_L100
## 3 geom_10m_fl1_L11 geom_10m_fl1_L11 geom_10m_fl1_L11 geom_10m_fl1_L11
## 4 geom_10m_fl1_L110 geom_10m_fl1_L110 geom_10m_fl1_L110 geom_10m_fl1_L110
## 5 geom_10m_fl1_L12 geom_10m_fl1_L12 geom_10m_fl1_L12 geom_10m_fl1_L12
## 6 geom_10m_fl1_L120 geom_10m_fl1_L120 geom_10m_fl1_L120 geom_10m_fl1_L120
## 7 geom_10m_fl1_L13 geom_10m_fl1_L13 geom_10m_fl1_L13 geom_10m_fl1_L13
## 8 geom_10m_fl1_L130 geom_10m_fl1_L130 geom_10m_fl1_L130 geom_10m_fl1_L130
## 9 geom_10m_fl1_L14 geom_10m_fl1_L14 geom_10m_fl1_L14 geom_10m_fl1_L14
## 10 geom_10m_fl1_L140 geom_10m_fl1_L140 geom_10m_fl1_L140 geom_10m_fl1_L140
## k 5
## 1 geom_10m_fl1_L10
## 2 geom_10m_fl1_L100
## 3 geom_10m_fl1_L11
## 4 geom_10m_fl1_L110
## 5 geom_10m_fl1_L12
## 6 geom_10m_fl1_L120
## 7 geom_10m_fl1_L13
## 8 geom_10m_fl1_L130
## 9 geom_10m_fl1_L14
## 10 geom_10m_fl1_L140
## [1] "10fold cv-error: 0.0370370370370371"
## [1] "For predictors geom_10m_fl1_L10 AND geom_10m_fl1_L100"
##
## preds 4 5
## 4 0 0
## 5 4 104
## [1] "Kappa overall = 0"
## [1] "Tau overall = 0.925925925925926"
## [1] "mean quality = 0.481481481481482"
## [1] "The quality is 0.481481481481482"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = NaN"
## [1] "###################### WITH PREDICTORS from the FW SELECTION ###################"
## [1] "10fold cv-error: 0.0370370370370371"
## [1] "For predictors geom_10m_fl1_L10 AND geom_10m_fl1_L100 AND geom_10m_fl1_L11 AND geom_10m_fl1_L110 AND geom_10m_fl1_L12 AND geom_10m_fl1_L120 AND geom_10m_fl1_L13 AND geom_10m_fl1_L130 AND geom_10m_fl1_L14 AND geom_10m_fl1_L140"
##
## preds 4 5
## 4 0 0
## 5 4 104
## [1] "Kappa overall = 0"
## [1] "Tau overall = 0.925925925925926"
## [1] "mean quality = 0.481481481481482"
## [1] "The quality is 0.481481481481482"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = NaN"
## [1] "10fold cv-error: 0.0370370370370371"
##
## preds 4 5
## 4 0 0
## 5 4 104
## [1] "Kappa overall = 0"
## [1] "Tau overall = 0.925925925925926"
## [1] "mean quality = 0.481481481481482"
## [1] "The quality is 0.481481481481482"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect

## [1] "######### Cramer's V = NaN"
## [1] "1d.4 - Potential for retention of water-soluble contaminants"
## [1] "Prediction error at end is: 0.584415584415584"
## [2] "Prediction error at end is: 0.575324675324675"
## [3] "Prediction error at end is: 0.584415584415584"
## [4] "Prediction error at end is: 0.584848484848485"
## [5] "Prediction error at end is: 0.575324675324675"
## [6] "Prediction error at end is: 0.566233766233766"
## [7] "Prediction error at end is: 0.548051948051948"
## [8] "Prediction error at end is: 0.548051948051948"
## [9] "Prediction error at end is: 0.548051948051948"
## [10] "Prediction error at end is: 0.548051948051948"
## k 1 k 2 k 3
## 1 geom_10m_fl8_L3 geom_10m_fl8_L3 geom_10m_fl1_L10
## 2 geom_10m_fl8_L4 geom_10m_fl8_L4 geom_10m_fl1_L100
## 3 geom_10m_fl10_L10 geom_10m_fl8_L5 geom_10m_fl1_L11
## 4 geom_10m_fl8_L5 geom_10m_fl10_L10 geom_10m_fl1_L110
## 5 geom_10m_fl10_L11 geom_10m_fl10_L11 geom_10m_fl1_L12
## 6 geom_10m_fl10_L12 geom_10m_fl10_L12 geom_10m_fl1_L120
## 7 geom_dtm_10m_hyd_fl5_L3 geom_10m_fl10_L13 geom_10m_fl1_L13
## 8 geom_10m_fl10_L13 geom_10m_fl10_L14 geom_10m_fl1_L130
## 9 geom_10m_fl8_L9 geom_10m_fl10_L15 geom_10m_fl1_L14
## 10 geom_10m_fl10_L14 geom_10m_fl10_L16 geom_10m_fl1_L140
## k 4 k 5
## 1 geom_10m_fl10_L10 geom_10m_fl1_L10
## 2 geom_10m_fl10_L11 geom_10m_fl1_L100
## 3 geom_10m_fl8_L50 geom_10m_fl1_L11
## 4 geom_10m_fl8_L60 geom_10m_fl1_L110
## 5 geom_10m_fl8_L3 geom_10m_fl1_L12
## 6 geom_10m_fl10_L12 geom_10m_fl1_L120
## 7 geom_10m_fl10_L13 geom_10m_fl1_L13
## 8 geom_10m_fl10_L14 geom_10m_fl1_L130
## 9 geom_10m_fl10_L16 geom_10m_fl1_L14
## 10 geom_10m_fl10_L17 geom_10m_fl1_L140
## [1] "10fold cv-error: 0.5"
## [1] "For predictors geom_10m_fl8_L3 AND geom_10m_fl8_L4"
##
## preds 1 2 3 4 5
## 1 40 10 9 8 2
## 2 0 0 0 0 0
## 3 0 0 0 0 0
## 4 7 4 8 14 6
## 5 0 0 0 0 0
## [1] "Kappa overall = 0.228877429591432"
## [1] "Tau overall = 0.375"
## [1] "mean quality = 0.164837625979843"
## [1] "The quality is 0.164837625979843"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = NaN"
## [1] "###################### WITH PREDICTORS from the FW SELECTION ###################"
## [1] "10fold cv-error: 0.564814814814815"
## [1] "For predictors geom_10m_fl8_L3 AND geom_10m_fl8_L4 AND geom_10m_fl10_L10 AND geom_10m_fl8_L5 AND geom_10m_fl10_L11 AND geom_10m_fl10_L12 AND geom_dtm_10m_hyd_fl5_L3 AND geom_10m_fl10_L13 AND geom_10m_fl8_L9 AND geom_10m_fl10_L14 AND geom_10m_fl10_L15 AND geom_10m_fl10_L16 AND geom_10m_fl1_L10 AND geom_10m_fl1_L100 AND geom_10m_fl1_L11 AND geom_10m_fl1_L110 AND geom_10m_fl1_L12 AND geom_10m_fl1_L120 AND geom_10m_fl1_L13 AND geom_10m_fl1_L130 AND geom_10m_fl1_L14 AND geom_10m_fl1_L140 AND geom_10m_fl8_L50 AND geom_10m_fl8_L60 AND geom_10m_fl10_L17"
##
## preds 1 2 3 4 5
## 1 47 14 17 22 8
## 2 0 0 0 0 0
## 3 0 0 0 0 0
## 4 0 0 0 0 0
## 5 0 0 0 0 0
## [1] "Kappa overall = 0"
## [1] "Tau overall = 0.293981481481481"
## [1] "mean quality = 0.087037037037037"
## [1] "The quality is 0.087037037037037"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = NaN"
## [1] "10fold cv-error: 0.564814814814815"
##
## preds 1 2 3 4 5
## 1 47 14 17 22 8
## 2 0 0 0 0 0
## 3 0 0 0 0 0
## 4 0 0 0 0 0
## 5 0 0 0 0 0
## [1] "Kappa overall = 0"
## [1] "Tau overall = 0.293981481481481"
## [1] "mean quality = 0.087037037037037"
## [1] "The quality is 0.087037037037037"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect

## [1] "######### Cramer's V = NaN"
## [1] "1d.5 - Potential as buffer for acidic contaminants"
## [1] "Prediction error at end is: 0.714718614718615"
## [2] "Prediction error at end is: 0.686147186147186"
## [3] "Prediction error at end is: 0.686580086580087"
## [4] "Prediction error at end is: 0.696103896103896"
## [5] "Prediction error at end is: 0.696103896103896"
## [6] "Prediction error at end is: 0.705194805194805"
## [7] "Prediction error at end is: 0.695670995670996"
## [8] "Prediction error at end is: 0.695670995670996"
## [9] "Prediction error at end is: 0.695670995670996"
## [10] "Prediction error at end is: 0.695670995670996"
## k 1 k 2 k 3
## 1 geom_10m_fl2_L12 geom_10m_fl2_L10 geom_10m_fl1_L16
## 2 geom_10m_fl4_L22 geom_10m_fl1_L5 geom_10m_fl1_L5
## 3 geom_dtm_10m_hyd_fl5_L90 geom_10m_fl2_L11 geom_10m_fl1_L17
## 4 geom_10m_fl2_L11 geom_10m_fl1_L8 geom_10m_fl1_L18
## 5 geom_10m_fl1_L12 geom_dtm_10m_hyd_fl5_L140 geom_10m_fl1_L15
## 6 geom_10m_fl4_L120 geom_dtm_10m_hyd_fl5_L150 geom_10m_fl1_L19
## 7 geom_dtm_10m_hyd_fl5_L100 geom_10m_fl4_L140 geom_10m_fl1_L20
## 8 geom_10m_fl1_L11 geom_10m_fl4_L150 geom_10m_fl1_L21
## 9 geom_10m_fl1_L13 geom_10m_fl2_L7 geom_10m_fl1_L22
## 10 geom_10m_fl1_L10 geom_10m_fl2_L8 geom_10m_fl1_L6
## k 4 k 5
## 1 geom_10m_fl3_L140 geom_10m_fl8_L3
## 2 geom_dtm_10m_hyd_fl5_L70 geom_10m_fl1_L100
## 3 geom_dtm_10m_hyd_fl5_L60 geom_10m_fl1_L11
## 4 geom_10m_fl4_L100 geom_10m_fl1_L110
## 5 geom_10m_fl4_L140 geom_10m_fl1_L120
## 6 geom_dtm_10m_hyd_fl5_L90 geom_10m_fl1_L13
## 7 geom_10m_fl4_L90 geom_10m_fl1_L130
## 8 geom_10m_fl4_L150 geom_10m_fl1_L14
## 9 geom_dtm_10m_hyd_fl5_L110 geom_10m_fl1_L140
## 10 geom_dtm_10m_hyd_fl5_L150 geom_10m_fl1_L15
## [1] "10fold cv-error: 0.62037037037037"
## [1] "For predictors geom_10m_fl2_L12 AND geom_10m_fl4_L22"
##
## preds 1 2 3 4 5
## 1 39 16 18 15 8
## 2 0 8 2 1 1
## 3 0 0 0 0 0
## 4 0 0 0 0 0
## 5 0 0 0 0 0
## [1] "Kappa overall = 0.136792452830189"
## [1] "Tau overall = 0.293981481481481"
## [1] "mean quality = 0.138392857142857"
## [1] "The quality is 0.138392857142857"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = NaN"
## [1] "###################### WITH PREDICTORS from the FW SELECTION ###################"
## [1] "10fold cv-error: 0.638888888888889"
## [1] "For predictors geom_10m_fl2_L12 AND geom_10m_fl4_L22 AND geom_dtm_10m_hyd_fl5_L90 AND geom_10m_fl2_L11 AND geom_10m_fl1_L12 AND geom_10m_fl4_L120 AND geom_dtm_10m_hyd_fl5_L100 AND geom_10m_fl1_L11 AND geom_10m_fl1_L13 AND geom_10m_fl1_L10 AND geom_10m_fl2_L10 AND geom_10m_fl1_L5 AND geom_10m_fl1_L8 AND geom_dtm_10m_hyd_fl5_L140 AND geom_dtm_10m_hyd_fl5_L150 AND geom_10m_fl4_L140 AND geom_10m_fl4_L150 AND geom_10m_fl2_L7 AND geom_10m_fl2_L8 AND geom_10m_fl1_L16 AND geom_10m_fl1_L17 AND geom_10m_fl1_L18 AND geom_10m_fl1_L15 AND geom_10m_fl1_L19 AND geom_10m_fl1_L20 AND geom_10m_fl1_L21 AND geom_10m_fl1_L22 AND geom_10m_fl1_L6 AND geom_10m_fl3_L140 AND geom_dtm_10m_hyd_fl5_L70 AND geom_dtm_10m_hyd_fl5_L60 AND geom_10m_fl4_L100 AND geom_10m_fl4_L90 AND geom_dtm_10m_hyd_fl5_L110 AND geom_10m_fl8_L3 AND geom_10m_fl1_L100 AND geom_10m_fl1_L110 AND geom_10m_fl1_L120 AND geom_10m_fl1_L130 AND geom_10m_fl1_L14 AND geom_10m_fl1_L140"
##
## preds 1 2 3 4 5
## 1 39 22 20 15 9
## 2 0 2 0 1 0
## 3 0 0 0 0 0
## 4 0 0 0 0 0
## 5 0 0 0 0 0
## [1] "Kappa overall = 0.0348139255702282"
## [1] "Tau overall = 0.224537037037037"
## [1] "mean quality = 0.0902857142857143"
## [1] "The quality is 0.0902857142857143"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect
## [1] "######### Cramer's V = NaN"
## [1] "10fold cv-error: 0.638888888888889"
##
## preds 1 2 3 4 5
## 1 39 24 20 16 9
## 2 0 0 0 0 0
## 3 0 0 0 0 0
## 4 0 0 0 0 0
## 5 0 0 0 0 0
## [1] "Kappa overall = 0"
## [1] "Tau overall = 0.201388888888889"
## [1] "mean quality = 0.0722222222222222"
## [1] "The quality is 0.0722222222222222"
## Warning in chisq.test(CM): Chi-squared approximation may be incorrect

## [1] "######### Cramer's V = NaN"